text:
Last year, independent power producers added 523.45 MW of wind plant in Canada, about 2% of the new wind capacity installed across the globe in 2008. Although the addition was less than an expected minimum of 700 MW, it was just enough to land Canada among the top ten countries for capacity increases. Canada ended the year with 2369 MW of wind power, placing it 11th in the world for total installed capacity.
"I think it was a good year. We had the second largest amount of installed capacity put in place in one year that we've ever had," says Robert Hornung, president of the Canadian Wind Energy Association (CanWEA). Only 2006 was better, with 775 MW installed.
Leading the way last year was Ontario, which added 291 MW to bring its tally to 782 MW. The province is set to keep its place as Canada's most active provincial market through 2009. It has nearly 400 MW more under construction and started the year by announcing power purchase agreements for six new wind farms, with a combined capacity of 492.1 MW. Last year also marked the installation of the first six wind projects built under the province's program of "standard offer" power purchase prices, which is designed to encourage connection of smaller wind projects to local networks.
Ontario explosion
But it is what is happening on the policy side that has the potential to see Ontario jump ahead. In the fall, Ontario energy minister George Smitherman called a halt to a regulatory review of the province's long term integrated power system plan by asking the Ontario Power Authority, the government agency responsible for electric system planning and procurement, to look at ways to bring more renewable energy online more quickly. Last month, Premier Dalton McGuinty offered the first hint of what is to come, telling a gathering in Toronto that his government will introduce legislation in the coming session designed to "unleash an explosion of new green energy" and create more than 50,000 jobs over the next three years.
Project developer Renewable Energy Systems Canada, one of the winners in Ontario's most recent round of wind power purchases, sees the province as one of Canada's key growth markets. "Quebec is going to go quiet for a few years," says the company's Peter Clibbon, reasoning that it will take some time for Canada's leading wind province to work through the projects selected from responses to its requests for proposals (RFPs). "Ontario, I think, is going to leap ahead in bounds and potentially have some of the most progressive legislation in Canada with the Green Energy Act, if what they say is true," he adds.
Quebec is planning to issue new RFPs this year for 500 MW of small-scale projects developed by municipalities and First Nations, although industry analysis shows the C$0.095/kWh cap on the price to be paid will deliver what CanWEA's Sean Whittaker calls an "unreasonably low" internal rate of return of around 4% that is unlikely to drive much investment. Prince Edward Island also plans to set in motion its 500 MW plan after delaying issuing an RFP in November because of the financial crisis fallout. British Columbia will award contracts this spring in its call for clean power, but has already served notice that declining demand in the face of the economic recession could cause it to buy less than it originally set out to.
The current financial environment is bound to have an impact, believes Hornung. Trouble accessing financing has already forced EarthFirst Canada, in the process of building a 144 MW project in British Columbia, to the brink of collapse. Early in February it said that if a sale of its assets could not be arranged by the end of that month, it would not have sufficient funds to continue to operate.
"We have seen in Canada, fortunately very limited so far, a few examples of wind developers who have come forward and said if we are in this situation we can't proceed," says Hornung. "That is part of the reason that, as we look ahead to 2009, our expectations are lower than they would have been a year ago. There is no doubt that for some projects the credit crisis will lead to delays, at a minimum."
Ben Isaacson, an alternative and renewable energy analyst with Scotia Capital, agrees. He says that while he remains bullish on the sector over the long term, there is "little doubt that poor credit and equity markets will continue to harm the growth prospects of many independent power producers over the short to mid-term."
Canadian alternative energy stocks decreased an average of about 70% in 2008, says Isaacson, dragged down by declines in global energy markets and a combination of higher debt financing costs and lower credit availability. The low share prices, he says, will likely cause companies to delay project-related equity offerings until stocks begin to recover, which could lead to wind project delays where contract terms allow it.
The situation, he says, has also left some companies whose stocks are trading at steep discounts to the value of their operating assets ripe for takeovers that would essentially allow buyers to acquire their development pipelines for free.
On the debt side, Isaacson says the implications of a frozen credit market for companies that typically target a capital structure of 80% debt and 20% equity are severe. "We believe that materially higher costs of borrowing, coupled with a limited availability of credit, will cause many attractive renewable power projects to be shelved or cancelled entirely." At the same time, though, Isaacson believes debt financing is still available to quality projects developed by companies with deep pockets or a proven track record.
Incentive shortfall
The waters have also been muddied by the Canadian government's decision not to provide new money to its ecoEnergy for Renewable Power (ERP) Program, which provides a C$0.01/kWh incentive for the first ten years of a project's life. The current funding could be fully allocated as early as spring, but certainly before the end of the year. Although the industry could get another shot at lobbying for an ERP expansion in 2009 if the Conservative government, which holds a minority of seats in parliament, is defeated and voters go to the polls yet again, the situation will make potential investors skittish.
"This does add uncertainty and what business always needs -- and particularly more so now than ever in our lifetimes -- is certainty," says John Keating, CEO of Calgary-based Canadian Hydro Developers.
The lack of a federal incentive could prompt provincial governments to rethink their renewable energy purchase plans, he says. And in Canadian Hydro's home province of Alberta, the only power market in Canada where new wind is not brought online through formal RFP processes, ERP is the only way to account for the environmental value of zero emissions technologies like wind.
"We'll have to see whether the forward price, without any significant carbon trading value, can make the economics work. The bottom line is until carbon is dealt with properly in the competitive marketplace, I think ecoEnergy should continue," he says.
Obama delay factor
Another policy issue Hornung expects to confront the industry in 2009 is in the area of greenhouse gas emissions reduction. The federal government has been working on a plan that includes emissions-intensity targets and an offset trading scheme that would provide another revenue stream for wind power projects. But with US president Barack Obama determined to finally map out a climate change response for his country, Canada could once again be thrown into limbo.
"I think there is a tremendous amount of uncertainty that has been reintroduced to the greenhouse gas discussion. The Conservative government has made it clear with the election of the Obama administration that it wants to pursue a North American approach to climate. It is also clear the Obama administration is keen to pursue a different kind of approach than the Conservatives have been doing to this point -- and any sort of North American negotiated approach is not something that will happen quickly," says Hornung.
"There's a real possibility the long-term result may be more powerful and beneficial as a result of cooperation between the two countries, but unfortunately I think there is a reasonably high probability it will lead to a delay in actually getting a carbon price signal in place in Canada."
Milestones in 2008
On the project development front, a key milestone in 2008 was the completion of the first utility-scale wind farms in both New Brunswick and Newfoundland & Labrador, leaving British Columbia as the only Canadian province without an operating wind farm. Nova Scotia Power announced contracts for seven wind projects totalling 244 MW, while New Brunswick Power signed deals for three projects with a combined capacity of 213 MW. Manitoba finalised a deal for a 300 MW project that will be the largest in the country.
Quebec, Canada's largest province in area, laid the foundation for the continued growth of its wind energy sector with the awarding of contracts for 2004.5 MW of new turbines to be supplied by Germany's Enercon and Repower Systems, both of which will set up factories in the province to make and assemble components. Prince Edward Island, the smallest province in Canada, announced its own C$1 billion strategy to install 500 MW of wind by 2013 and build a new transmission cable to carry it to markets on Canada's mainland and south into the US Northeast. For a province with an average load of 160 MW it is a very ambitious goal and "a clear example of the kind of big thinking we would like to see," says Hornung.
The big winner among wind turbine suppliers last year was GE Energy, which supplied technology to two projects representing 46% of Canada's 2008 capacity additions. Vestas machines were used in eight projects with a 35% market share. Siemens saw its technology used for the first time in Canada, in one project representing 19% of the total installed.


text:
Smoking on film has declined since 2005, but cigarettes are still featured in far too many films, according to a new report.
The common practice could influence young people to smoke and should be countered by warnings before such films, say the study's authors.
"The results of this analysis indicate that the number of tobacco incidents peaked in 2005, then declined by approximately half through 2009, representing the first time a decline of that duration and magnitude has been observed," the team at the U.S. Centers for Disease Control and Prevention, the University of California San Francisco and elsewhere wrote.
U.S. & World
"However, nearly half of popular movies still contained tobacco imagery in 2009, including 54 percent of those rated PG-13, and the number of incidents remained higher in 2009 than in 1998," they added in the CDC's weekly report on death and illness.
Congressmen Edward Markey and Joseph Pitts, who both serve on the Energy and Commerce Committee, wrote the Motion Picture Association of America encouraging the industry to adopt stronger anti-smoking measures.
"Exposure to onscreen smoking in movies increases the probability that youths will start smoking. Youths who are heavily exposed to onscreen smoking are approximately two to three times more likely to begin smoking than youths who are lightly exposed," the CDC report reads.
The researchers counted each time tobacco use was shown in the biggest-grossing films of 1991 to 2009.
"This analysis shows that the number of tobacco incidents increased steadily after the 1998 Master Settlement Agreement between the state attorneys general and the major cigarette companies, in which the companies agreed to end brand placement," they wrote.
Selected Reading: Newsweek, Reuters, American Cancer Society.

subset: commoncrawl


text:
This family-run company has offered escorted tours for decades, and today Tauck operates an assortment of river cruises on the world's famous waterways. Tauck's ships deliver a deluxe experience, with well-appointed accommodations and daily activities that include informative lectures and cultural performances.
As with Tauck's land vacations, the company's river cruises are highly inclusive. The cost of your cruise includes your accommodations, most meals on and off the ship, entertainment, shore excursions, and all gratuities and taxes. Wine, beer and soft drinks are included with fine European-style dinners.
Each sailing has at least one Tauck Cruise Director and perhaps more, depending on the number of guests. Shore excursions are led by Directors and local guides.
Click any river cruise below for the itinerary, dates and prices.
Copyright © 2020 by Vacations To Go. All rights reserved. CST 2072920-50


text:
Brian Beutler introduces Speaker Boehner's strongest bit of leverage in the fiscal cliff discussions:
The debt limit hike isn't actually a variable in the budget math concentrating Democratic and Republican minds ahead of 2013. But when Congress raises it and in what context has huge implications for the ultimate shape of the tax and safety net reforms the parties settle upon.
Ignore the need to raise the debt ceiling for now, and Democrats have all of the near-term leverage. If Republicans don't agree to increase tax rates on wealthy people, everyone's taxes will increase significantly automatically, and they'll have to cut middle-income taxes — but not upper-income taxes — retroactively.
But, as Senate Majority Harry Reid (D-NV) and others have noted, that means Republicans could turn right around and demand huge concessions from Democrats in exchange for raising the debt ceiling. If that happens, the White House has indicated it will call Boehner's bluff. Force him to raise the debt limit cleanly, or tank the U.S. and global economies. But if they lacked the nerve, Boehner could walk away with another huge pot of concessions from Democrats.
Meanwhile, The Atlantic's Derek Thompson proposes eliminating the debt ceiling altogether.
I won't go nearly that far, but there should be a word of caution for conservatives. We claim to be the party of the economy and the middle class, the party of economic certainty, and the party that stays out of the way of "job creators."
That goes out the window when we permit government shutdowns and create immense uncertainty for entrepreneurs and consumers alike.
Negotiate like hell (or perhaps madmen), but at the end of the day, we're fighting to improve peoples' lives. Wreaking havock by waging ideological warfare is neither the way to win elections nor something our party should desire.


text:
Cyan Worlds, Inc.
Rand and Robyn Miller changed the way people play computer games. When the enigmatic Myst arrived a decade ago, competition gave way to curiosity, and millions booted up to explore lush forests, ancient cities, and mysterious ports. Now, following the hit sequel Riven and Real Myst, a real-time version of the original, Rand and the rest of his team at Cyan are at it again with Uru: Ages Beyond Myst. The 3-D game taps into the Net's virtual community and turns Miller's trademark environments into persistent worlds. Players can venture in alone or meet up with friends online to solve puzzles, play chess, and go on scavenger hunts, communicating in real time via instant messaging or voice over IP. Uru debuts at the Electronic Entertainment Expo in May before hitting shelves later this year. Rand took Wired on an exclusive tour of his mystifying new world.
This article has been reproduced in a new format and may be missing content or contain faulty links. Contact email@example.com to report an issue.
WIRED: How did the project get started?
RAND MILLER: Most games are like sports. Myst, Riven, and Uru are story-driven. You're always wondering what you're going to see next. Well, what if every night there was something new?
Don't other massively multiplayer online games offer something new every night?
We don't consider this a massively multiplayer online game. I've played a lot of Dark Age of Camelot and it's loads of fun, but long-run games like that aren't sustainable. At some point you realize that you're doing the same things over and over. We wanted to create new places continuously and then add gameplay to them. We wanted to give players the option – not given in MMOGs – to either interact with others or explore alone.
From a development perspective, how does Uru go beyond Myst and Riven?
We wanted a true persistent world. If you walk into a room, turn on a light, and then leave, when someone else comes along three days later that light should still be on. There are a lot of games that clean up after themselves. If you open a door, it closes itself. If you kill a monster, it eventually disappears. That's not what we wanted. We also wanted a real physics engine. If you kick a ball, how far will the ball roll, and where will it stop? In a 3-D environment, that's been really difficult to do.
Did you draw from real-life locations when designing Uru's look?
I recently took my daughters to Glacier National Park. There's a cozy feeling when the fog rolls in, or when you're in the forest, surrounded. We tried to get that essence into the game.
Do you think Uru will attract a whole new crop of fans with different ideas about gaming?
We don't want people playing this game 40 hours a week. We don't want people to become obsessed with it. We want them to say, "I wonder what's going to happen tonight?" So we're scheduling events. You can also take pictures of where you are and send the images to friends in the game.
How interactive will Uru be?
There's a fine line between making an interactive environment and making everything within it interactive. After Myst we got a lot of mail from people complaining about the red herrings. For instance, there's a bird that you can get to sing, but to no end. Not everything is meaningful.
The other games had definite endings. Will there be one to Uru?
Yes. We haven't decided what yet, but there will be a conclusion to the story, a payoff.


text: Sizzlingsirens.com is going to be the only site you visit when what you crave is beautiful women with the desire to play with their juicy pink pussies and tight ass holes hoping to have you jerk your cock hard and spill a delicious load of your warm creamy cock milk for their cum thirsty mouths. For as little as $10.00, you can have exclusive access to these lovely ladies and their beautiful pink slits and round tight asses. Come get in on the action today.


text:
The Huw Stephens (pictured) curated SWN festival is getting better man! As the Gallaghers may or may not be saying any longer. This time over 50 bands (56 in total!) have been added to the already bulging bill with Pulled Apart By Horses, Johnny Foreigner, Catherine AD, Ungdomskulen and Internet Forever among the notables.
50 is quite a lot to list in linear form, so here are some of the most interesting and exciting bands from that list. You can check the full list of bands who have been confirmed for Swn on the official website.
Anchorsong, An Experiment on a Bird in the Air Pump, Bright Light Bright Light, Catherine AD, Chris TT, Drums Of Death E and E. Ellie Hurricane, Geraint Williams, Gideon Conn, Glass Diamond, Internet Forever, James Tyson, Jonquil, Katell Keineg, Master Shortie, Not Cool, Our Brother The Native, Paper Aeroplanes, Portasound, Pulled Apart By Horses, Rose Elinor Dougall, Slow Club, Soft Toy Emergency, Stornoway, Swanton Bombs, The Death of Her Money, The Irascibles, The Longcut, The Pipettes, The Young Republic, Tom Brosseau, Tubelord, Ungdomskulen, Yndi Halda, Y Promatics, Zimmermans AND Zun Zun Egui.
Below is a video for Norway's Ungdomskulen. This one video and song should make you want to either a) become part of Ungdomskulen or b) buy tickets for SWN, so you can watch 'em live.
Other bands who were on the line-up already included these rag-tag bunch:
Los Campesinos!, Dananananaykroyd, Copy Haho, Sparky Deathcap, Gold Panda, Daedelus, Munch Munch, The Leisure Society, Sweet Baboo, Lucky Soul, Sons of Noel And Adrian, Cymdeithas Yr Hobos Unig, Hail! The Planes, Huw M, Minotaur Shock, Girls, Broken Family Band, Three Trapped Tigers, Strange News From Another Star, John Grindell, The Twilight Sad, Pencadlys, Anchorsong, Nos Sadwrn Bach, Mary Anne Hobbs, Johnny Foreigner, Talons, Mitchell Museum, Threatmantics, Wet Dog, Supertennis, Tim And Sams Band with Tim and Sam, The Victorian English Gentlemens Club, Zissou, Y Pencadlys, Goldheart Assembly, Marina And The Diamonds AND...Totally Enormous Extinct Dinosaurs.
SWN takes place across multiple Cardiff city centre venues from October 22-24. Tickets are available from here.
Or, if you're in the area (of Wales), you can get wristbands (17 quid for one day, 45 for the weekend) for SWN from these places.
Spillers Records / Cardiff (029) 20224905
Diverse Records / Newport (01633) 259661
Kooki Two Bit / Splott / (029) 20489352
Chapter Arts Centre / Cardiff (029) 20311050
Catapult Records / Cardiff (029) 20
The Gate / Cardiff (029) 20483344
Cardiff University Students Union (029) 20781458
Andy's Records – Aberystwyth – 01970624581
Cob Records – Bangor – 01248353020


text:
I received a email saying that I would need to check again within 12 hours. However when I check my ETA status at http://www.eta.immi.gov.au/
I got this:
You have a current ETA to travel to Australia.
The Australian Electronic Travel Authority System has reported the following data and conditions apply to your ETA:
Expiry Date 05 JUN 2013 Period of Stay 3 Months Number of Entries Multiple Employment Conditions Employment Prohibited
The Expiry Date of the ETA is the latest date on which you may enter Australia with this ETA. The Period of Stay is the longest time you may spend in Australia on any one visit. The Number of Entries is the number of times you may enter Australia with this ETA.
Am I approved or not?


text:
New twist in Twitter harassment case
TORONTO — The so-called Twitter case — what appears to be the first time in Canada someone has been charged with criminal harassment based entirely on tweets — has taken an odd and unexpected turn.
Ontario Court Judge Brent Knazan came into court Thursday to announce he had received a letter from a stranger making the startling allegation the complaint he is hearing "is fraudulent, or worse."
Greg Elliott of Toronto, 53, is charged with criminally harassing three women, though the Toronto Police officer in charge of the case, Det. Jeff Banglid, already has testified he found no overt threats or sexual overtures in Elliott's tweets to any of the complainants.
The first one, 29-year-old Steph Guthrie, an articulate political activist, was on the witness stand when the trial first adjourned in January.
According to the letter, parts of which the judge read aloud in open court, the person claimed to be a former acquaintance of the three complainants and alleges they "conspired, in my presence, to fabricate a criminal harassment complaint" against Elliott.
The person also alleged the conspiracy extends "to the ministry of the attorney-general," information relayed in the summer of 2012 by two of the complainants' friends.
Judge Knazan said the letter, which he received Tuesday, was signed and provided contact information.
But he kept the writer's name and gender out of the public domain, in case the person was well-intentioned or was unaware it's inappropriate to write to judges.
Neither did the judge read aloud the names of the two complainants' friends mentioned in the letter or its first paragraph, in which the writer explained the reason for writing.
Still, the judge said, the "allegations leave police and Crown counsel no option but to investigate," and adjourned the case until its next scheduled date in May.
Interestingly, according to the Criminal Code of Canada, a criminal harassment charge appears to be rooted as much in the alleged victim's perception of the offending conduct as in the alleged conduct itself.
(I also received a copy of the letter to the judge, sent by email last week, before the judge got his. I attempted to reach the writer via the contact information included, but neither phone number nor email worked.)
When the case previously adjourned two months ago, Guthrie was in mid-cross-examination by Chris Murphy, Elliott's lawyer.
Murphy had questioned her at length about a meeting in the summer of 2012, when a group of people, including the other complainants and a couple of their friends, gathered to decide, as she put it once, "how as a community we could respond to predatory and harassing behaviour of men," including allegedly Elliott, on Twitter.
One of the friends whom Guthrie identified as being at the meeting is one of the two named in the letter and alleged by the writer to be knowledgeable about the purported conspiracy.
When the meeting ended, Murphy alleged in January, the attendees "had a plan to deal with Mr. Elliott … Each of them had a role."
At one point, he told the judge, "It may be that at that meeting, a conspiracy to commit a criminal offence took place — to criminally harass Mr. Elliott, to commit mischief and interfere with his ability to enjoy Twitter."
Given that all this happened well in advance of the letter being sent — the judge's announcement and the letter appeared to take both Murphy and Crown attorney Marnie Goldenberg completely by surprise — it renders at least some of the writer's allegations relevant and appears to lend them a little heft.
Were the people at the meeting — all the complainants attended, remember — just talking about what they could do to stem the oft-misogynistic ramblings on Twitter or did they hatch a plan to target Elliott, to make an example of him?
Certainly, the self-possessed Guthrie has admitted to "outing" others she deemed to be creeps.
She was questioned extensively about her decision to publicly shame a 25-year-old man from Sault Ste. Marie, Ont., who had invented a "beat up Anita Sarkeesian" video game, where users could punch an image of the feminist video blogger until the screen, and her face, turned red.
Guthrie had wondered aloud on the web if she should blow the whistle on the man, or, as she put it, "So I found the Twitter account of that f— listed as creator of the 'punch a woman in the face' game," she tweeted. "Should I sic the Internet on him?"
When the answer was a resounding "Yes!," she tweeted a link to the story about the game "to prospective Sault Ste. Marie employers" and the local newspaper.
As Murphy put it to her in January, "This was another case that rose to the level where you agreed with online vigilantism" and accused her of wanting to ruin the man's life.
"I was simply making people aware," Guthrie replied, but she acknowledged if others took action that ruined his life, "I would not feel sorry about that."


text:
Previous Chapter | Table of Contents | Next Chapter
Permanent Disability
When Feng Yu Heng revealed her set of tools, Song Kang nearly dove forward and kneeled to her.
"This… this is…" He began to stutter, staring at the set of things wide-eyed. He recognized some things, while there were others that he did not, but even if he did not recognize them, he had spent over a decade researching the things that Feng Yu Heng had called surgical tools. How could he not understand that these were all top-tier tools used in the secret technique!
Song Kang's entire body trembled. He was truly too moved. These things that only existed in his imagination, and some that did not even exist in his imagination, were actually placed directly in front of him. Song Kang did not have time to worry about where Feng Yu Heng pulled these items from. He just hoped that these things could belong to him!
He subconsciously reached out to snatch them, but who knew that Feng Yu Heng would move her sleeve and, like magic, immediately made the set of tools disappear from in front of Song Kang.
The hand that Song Kang had extended came up empty and crashed onto the table.
He could not accept this reality. He looked like the Feng family's matriarch when someone had placed money in front of her then taken it away. Clawing at the table with all ten fingers, it was as though he was trying to scratch the tools out of the wood.
Xuan Tian Ye, who was lying in bed, saw him like this and could not help but angrily shout: "You worthless thing!"
This shout gave Song Kang a reminder, as his nerves shook. He seemed to have realized something and turned to look at Xuan Tian Ye. He then looked at Feng Yu Heng, and his mind began to recall the things that he had heard related to this county princess Ji An on his way to the capital from the North. He had heard that she had mystical hands that could save someone from death.
In truth, Feng Yu Heng had not truly saved that many people with her own two hands. In fact, she had never gone out of the capital to treat anyone's illness. But the one that was spread around the most was her most mystical achievement. It was when she had revived a person that had already died in front of Hundred Herb Hall. There was also Princess Xiang, who had been ill for a long time without getting better. Fortunately, after county princess Ji An finished taking care of her, the third prince used an entire jade mine to express his thanks.
These two things were spread by the citizens as being miracles, especially the time when she had revived a dead person. That was too deeply rooted in the hearts of people.
Song Kang had heard this the entire time and thought that they were just rumors, but when he heard what Feng Yu Heng had said, and he had seen the tools that she had revealed, Song Kang suddenly understood that the citizens were being reserved in their rumors. The secret techniques that he had seemed to be nothing compared to what county princess Ji An had. She did not appear shocked, and she casually pointed out the problems that he had struggled with.
He had some guesses in his mind. After thinking a little, he asked Feng Yu Heng: "You said that disinfecting is a must, and tools are a must, then what must be done after performing the secret technique? Do you know what will happen after?"
Feng Yu Heng corrected him: "It's called surgery. It's not called a secret technique. Not preparing professionally beforehand, using incorrect surgical methods, using an unsuitable transplant organ and not monitoring the situation closely after the surgery will directly result in postoperative complications. Once these complications arise, based on your ability, there is no chance of reversing the desperate situation."
She used the term professional, which Song Kang did not quite understand, but he was a smart person. In this sort of era, he was able to study some incomplete images and research the basic foundations of surgery. How would he not have the ability to analyze what Feng Yu Heng's words meant. Moreover, the so-called postoperative complications were things that he had experienced before many times. Everything was clearly going very well, but the person that had been treated suddenly experienced a change, as all kinds of situations arose, leaving him quite helpless.
Song Kang stared straight at Feng Yu Heng, his eyes filled with expectation. It was the same look that a starving wolf had when seeing a piece of meat. He looked like he was about to pounce at any moment.
Xuan Tian Ming became unhappy, "What are you looking at?"
Song Kang did not react.
Xuan Tian Ming had never been someone with any patience. Aside from Feng Yu Heng and imperial concubine Yun, he would lose his temper at the drop of a hat. Song Kang ignored him, so he just kicked at him without another word, kicking into the cabinet. This caused blood to seep from the corner of his lips.
Feng Yu Heng did not say anything. In order to satisfy his own curiosity, this ghost doctor harmed countless living people. Kicking him to death was something that ought to be done.
But Song Kang was a very tenacious person. Although he had been very badly injured, he did not give up, and he did not get angry. He barely managed to get up and simply crawled over to Feng Yu Heng. He then placed his hands on the ground and kowtowed with his forehead touching the ground. It was like he was devoutly kneeling to her.
Xuan Tian Ming shrugged and expressed that there was nothing that he could do.
Feng Yu Heng coldly looked down, asking Song Kang: "When he kicked you, did it hurt?"
Song Kang nodded, speaking truthfully: "Yes."
"Then think about it, taking bones and organs from a living body, how did that person die?" Feng Yu Heng's words had two layers of meaning. One layer was condemnation, and the other was for Song Kang to figure out.
Song Kang was a very direct person. There was only one track in his mind. Aside from focusing on medicine, there was nothing else in this life that interested him. Condemnation and taking bones from a living body were not things that he considered. His mind jumped straight to the second meaning, "You mean to say… they died of pain?"
Another kick went flying, and Song Kang was kicked a long distance. Xuan Tian Ming then said: "You keep saying you. Who are you speaking to?"
Song Kang immediately reacted, quickly changing his words: "County princess!"
Feng Yu Heng knew that this person did not have a heart. He had personally killed that many people, yet there was no sense of pity. An angry expression appeared on her face.
Song Kang did not notice this. He just crawled back over to Feng Yu Heng's feet and repeatedly said: "I know that mafeisan was completely useless. Perhaps it is effective when cutting into flesh, but when the bone is touched, it instantly loses all effectiveness. It's not just the living body. It's also the patient. The majority of them die from pain. But I searched the world for a better mafeisan, yet they were still useless!"
He whispered to himself and had already entered his own world. In that world, Feng Yu Heng had given him that set of tool and a special mafeisan. She even taught him a better method than the secret technique in the drawings. From that point onward, when he practiced medicine, aside from county princess Ji An, he would be unmatched.
Song Kang suddenly woke up and instantly thought of an idea. He raised his head and looked at Feng Yu Heng, suddenly saying: "I beg county princess take me in as an apprentice!"
At this time, Duan Mu Qing, who had been standing at the door for a long time, was finally unable to endure continuing to listen. Angrily rushing in, he pulled out his sword and swung at Song Kang's head. Unfortunately, before he could finish his slash, his wrist was caught by a whip.
He turned and glared at Xuan Tian Ming: "Your Highness, Song Kang is someone from the North. Even if this lowly official is in the capital, this lowly official has the right to dispose of him, right?"
Feng Yu Heng practically wanted to laugh. Had Duan Mu Qing become muddled by anger? He actually wanted to reason with Xuan Tian Ming!
Sure enough, Xuan Tian Ming said: "Everything in this world belongs to the imperial family. Could it be that the three northernmost provinces do not belong to Da Shun?"
Duan Mu Qing was rendered completely speechless. He just felt a force act on the whip, as he was thrown out!
Fortunately, he had some ability, and he was not left in as bad a situation as Song Kang. Unfortunately, what could he do just with remaining standing? The ghost doctor that he had brought back to the capital to treat Xuan Tian Ye was still kneeling at Feng Yu Heng's feet, repeatedly kowtowing. It was like he was a devout believer worshipping his god. He was completely single-minded.
Feng Yu Heng, however, no longer paid any attention to Song Kang. Instead, she stood up and went to Xuan Tian Ye's side. With a faint smile, she said to him: "The engagement note for Feng family's daughter of a concubine, Feng Chen Yu, I have already brought to the Xiang Palace. I really must congratulate third brother. But I just don't know if I should call you brother-in-law or third brother the next time we meet." While saying this, she turned around and pointed at the wheelchair that was pushed in: "This is the one his Highness the ninth prince used before. We felt that there must be a succession of these things. Right now, his Highness the ninth prince's legs have healed, and it just happened that third brother's legs are crippled. That's why I decided to bring it to the Xiang Palace. It is a gift to third brother."
While she spoke, she smiled brightly. It was as aggravating as possible. Xuan Tian Ye truly did not want to bicker with a lying girl, thus he simply looked away.
But Feng Yu Heng was someone that was paid attention to such things, saying: "No matter how it is, your marriage will still need to happen. As a younger sister, I cannot bear to watch you welcome someone new while lying down, so…"
Duan Mu Qing's eyes lit up, as he heard Feng Yu Heng say: "I can at least treat you to the point where you can at least sit in a wheelchair." He let out a sigh of relief.
Xuan Tian Ming did not ask Feng Yu Heng why she would be treating old third. As he saw it, anything that his wife did was correct. In fact, when Feng Yu Heng said to Song Kang: "I will treat him. You come and help." He believed that this was correct.
In truth, Feng Yu Heng's treatment of Xuan Tian Ye did not take long, as it only lasted from when she promised to the evening of that same day.
Duan Mu Qing had been kicked out of the room along with the servants of the Xiang Palace. This left only Feng Yu Heng, Xuan Tian Ming, ghost doctor Song Kang along with Wang Chuan and Huang Quan.
Being able to receive this opportunity, Song Kang was not just very happy. He devoutly remained at Feng Yu Heng's side, listening to her point at Xuan Tian Ye's body and analyze the situation. He then watched her very impolitely remove the bandages around his knees without any care for the pain that Xuan Tian Ye felt. She then used her small hands to forcefully squeeze the bone that had just been transplanted.
"Since it has already been connected, I will not process it any further, but Song Kang, I will tell you," Feng Yu Heng coldly said: "Connecting bones is not all about connecting bones. There are also the broken tendons, ligaments and blood vessels. Also, your technique when connecting this bone was incorrect. Although he will be able to move it in the future, he will not be able to put any weight on it. The knee is a major joint. If this major joint cannot hold any weight, he will not be able to stand."
Song Kang was like a young student, listening very attentively. He then followed up with a question: "Master, then are you able to reconnect this bone?"
Feng Yu Heng looked at him sideways, reminding him: "I am not your master. If you call me that again, I will kick you out." Seeing Song Kang nod and accept this, she then said: "I can treat him completely, and there would be no need for human bones. There are times when a special material can be used to create a fake joint. As long as it is placed properly, it can replace and restore the joint's original function. It's just that…" She squinted her eyes and looked at Xuan Tian Ye, who was lying in bed with a bit of an expectant look, saying: "You want to stand up, right? Don't worry, I will not treat you. This county princess is kind and will give you the ability to welcome your bride while sitting. I will not be responsible for anything else."
Xuan Tian Ming spoke from the side, saying: "That's right, the suffering that this great one went through, everyone must have a taste."
Feng Yu Heng giggled, saying to Xuan Tian Ye: "Yours will be a permanent disability!"


text:
Felix Wang 3d topped the table at the Bracknell tournament May 9 in Wokingham, UK. British Go Association president Jon Diamond 4d (r) took silver, based on SOS ahead of Francis Roads 3d, who won bronze. Also Helen Harvey 3k, Elinor Bracks 8k, and Malcolm Law 10k went 3-0 in the field of 42.
– Peter Dijkema, EJ European Correspondent


text:
You are currently browsing the category archive for the 'Operations' category.
IBM redesigned its business intelligence platform, now called IBM Cognos Analytics. Expected to be released by the end of 2015, the new version includes features to help end users model their own data without IT assistance while maintaining the centralized governance and security that the platform already has. Our benchmark research into information optimization shows that simplifying access to information is important to virtually all (97%) participating organizations, but it also finds that only one in four (25%) are satisfied with their current software for doing that. Simplification is a major theme of the IBM Cognos redesign.
The new IBM Cognos Analytics provides a completely Web-based environment that is consistent in the user interface and security across multiple devices and browsers. The redesigned interface follows IBM's internal cultural shift to base product development first on the user experience and second on features and functionality. This may be a wise move as our research across multiple analytic software categories finds usability to be organizations' most often important buying criterion.
The redesign is based on the same design and self-service principles as IBM Watson Analytics which we did award a Ventana Research Technology Innovation Award for 2015 in business analytics. The redesign is most evident in the IBM Cognos Analytics authoring mode. The Report Studio and Cognos Workspace Advanced modules have been replaced with a simplified Web-based modeling environment. The extended capabilities of IBM Cognos 10.2.2 are still available, but now they are hidden and more logically arranged to provide easier user access. For example, the previous version of Cognos presented an intimidating display of tools with which to do tasks such as fine-grain manipulation of reports; now these features are hidden but still easily accessible. If a user is having difficulty finding a particular function, a "smart search" feature helps to find the correct menu to add it.
The new system indexes objects, including metadata, as they are created, providing a more robust search function suitable for nontechnical users in the lines of business. The search feature works with what IBM calls "intent-based modeling" so users can search for words or phrases – for example, revenue by unit or product costs – and be presented with only relevant tables and columns. The system can then automatically build a model by inferring relationships in the data. The result is that the person building the report need not manually design a multidimensional model of the data, so less skilled end users can serve themselves to build their own data models that underpin dashboards and reports. Previously, end users were limited to parameterized reporting in which they could work only within the context of models previously designed by IT. Many vendors of analytics have been late in exploiting the power of search and therefore may be missing a critical feature that customers desire. Ventana Research is a proponent of such capabilities; my colleague Mark Smith has written about them in the context of data discovery technology. Search is fundamental to user-friendly discovery systems, as is reflected in the success of companies such as Google and Splunk. With search becoming more sophisticated, being based on machine-learning algorithms, we expect it to become a key requirement for new analytics and business intelligence systems.
Furthering the self-service aspect is the ability for end users to access and combine multiple data sets. The previous version of IBM Cognos (10.2.2) allowed users to work with "personal data sets" such as .csv files, but they needed an IBM DB2 back end to house the files. Now such data sets can be uploaded and managed directly on the IBM Cognos Analytics server and accessed with the new Web-based authoring tool. Once data sets are uploaded they can be accessed and modeled like any other object to which the user has access. In this way, IBM Cognos Analytics addresses the "bring your own data" challenge in which data sources such as personal spreadsheets must be integrated into enterprise analytics and business intelligence systems.
After modeling the data, users can lay out new dashboards using drag-and-drop capabilities like those found in IBM Watson Analytics. Dashboards can be previewed and put into service for one-time use or put into production mode if the user has such privileges. As is the case with IBM Watson Analytics, newly designed dashboard components such as tables, charts and maps are automatically linked so that changes in one part of the dashboard automatically relate to other parts. This feature facilitates ease of use in designing dashboards. Some other tools in the market require widgets to be connected manually, which can be time-consuming and is an impediment to prototyping of dashboards.
The move to a more self-service orientation has long been in the works for IBM Cognos and so this release is an important one for IBM. The ability to automatically integrate and model data gives the IT department a more defensible position as other self-service tools are introduced into the organization and are challenging data access and preparation built within tools like IBM Cognos. This is becoming especially important as the number and complexity of data sources increases and are needed more rapidly by business. Our research into information optimization shows that most organizations need to integrate at least six data sources and some have 20 or more sources they need to bring together. All of which confirms what our data and analytics in the cloud benchmark research finds data preparation to be a top priority in over half (55%) of organizations.
Over time, IBM intends to integrate the capabilities of Cognos Analytics with those of Watson Analytics. This is an important plan because IBM Watson Analytics has capabilities beyond those of self-service tools in the market today. In particular, the ability to explore unknown data relationships and do advanced analysis is a key differentiator for IBM Watson Analytics, as I have written. IBM Watson Analytics enables users to explore relationships in data that otherwise would not be noticeable, whereas IBM Cognos Analytics enables them to explore and put into production information based on predefined assumptions.
Going forward, I will be watching how IBM aligns Cognos Analytics with Watson Analytics, and in particular, how Cognos Analytics will fit into the IBM cloud ecosystem. Currently IBM Cognos Analytics is offered both on-premises and in a hosted cloud, but here also IBM is working to align it more closely with IBM Watson Analytics. Bringing in data preparation, data quality and MDM capabilities from the IBM DataWorks product could also benefit IBM Cognos Analytics users. IBM should emphasize the breadth of its portfolio of products including IBM Cognos TM1, IBM SPSS, IBM Watson Analytics and IBM DataWorks as it faces stiff competition in enterprise analytics and business intelligence from a host of analytics companies including new cloud-based ones. IBM is rated a Hot Vendor in our Ventana Research Analytics and Business Intelligence Value Index in part because of its overall portfolio.
For organizations already using IBM Cognos, the redesign addresses the need of end users to create their own dashboards while maintaining IT governance and control. The new interface may take some getting used to, but it is modern and more intuitive than previously. For companies new to IBM Cognos, as well as departments wanting to take a look at the platform, cloud options offer less risk. For those wanting early access to the new IBM Cognos Analytics, IBM has provided access to it on www.analyticszone.com. The changes I have noted move IBM Cognos Analytics closer to the advances in analytics as a whole, and I recommend that all these groups examine the new version.
Ventana Research
Tableau Software's annual conference, which company spokespeople reported had more than 10,000 attendees, filled the MGM Grand in Las Vegas. Various product announcements supported the company's strategy to deliver value to analysts and users of visualization tools. Advances include new data preparation and integration features, advanced analytics and mapping. The company also announced the release of a stand-alone mobile application called Vizable . One key message management aimed to promote is that Tableau is more than just a visualization company.
Over the last few years Tableau has made strides in the analytics and business intelligence market with a user-centric philosophy and the ability to engage younger analysts who work in the lines of business rather than in IT. Usability continues to rank as the top criteria for selecting analytic and business intelligence software in all of our business analytics benchmark research. In this area Tableau has introduced innovations such as VizQL, originally developed at Stanford University, which links capabilities to query a database and to visualize data. This combination enables users not highly skilled in languages such as SQL or using proprietary business intelligence tools to create and share visually intuitive dashboards. The effect is to provide previously unavailable visibility into areas of their operations. The impact of being able to see and compare performance across operations and people often increases communication and knowledge sharing.
Tableau 9, released in April 2015, which I discussed, introduced advances including analytic ease of use and performance, new APIs, data preparation, storyboarding and Project Elastic, the precursor to this year's announcement of Vizable. Adoption of 9.x appears to be robust given both the number of conference attendees and increases in third-quarter revenue ($170 million) and new customers (3,100) reported to the financial markets.
As was the case last year, conference announcements included some developments already on the market as well as some still to come. Among data preparation capabilities introduced are integration and automated spreadsheet cleanup. For the former, being able to join two data sets through a union function, which adds rows to form a single data set, and to do integration across databases by joining specific data fields gives users flexibility in combining, analyzing and visualizing multiple sets of data. For the latter, to automate the spreadsheet cleanup process Tableau examined usage patterns of Tableau Public to learn how users manually clean their spreadsheets. Then it used machine-learning algorithms to help users automate the tasks. Being able to automatically scan Excel files to find subtables and automatically transform data without manual calculations and parsing will save time for analysts who otherwise would have to do these tasks manually. Our benchmark research into information optimization shows that data preparation consumes the largest portion of time spent on analytics by nearly half (47%) of organizations and even higher in our latest data and analytics in the cloud benchmark research by 59 percent of organizations.
Advanced analytics is another area of innovation for Tableau. The company demonstrated developments in outlier detection and clustering analysis natively integrated with the software. Use of these features is straightforward and visually oriented, replacing the need for statistical charts with drag-and-drop manipulation. The software does not enable users to identify numbers of segments or filter the degree of the outliers, but the basic capability can reduce data sets to more manageable analytic sets and facilitate exploration of anomalous data points within large sets. The skill necessary for these tasks, unlike the interpretation of box plots introduced at last year's conference, is more intuitive and better suited for business users of information.
The company also demonstrated new mapping and geospatial features at the conference. Capabilities to analyze down to the zip code on a global basis, define custom territories, support geospatial files, integrate with the open source mapping platform MapBox and perform calculations within the context of a digital map are all useful features for location analytics, which is becoming more important in areas such as customer analytics and digital devices connected in the emerging Internet of things (IoT). Tableau is adding capabilities that participants most often cited as important in our research on location analytics: to provide geographic representation (72%), visualize metrics associated with locations (65%) and directly select and analyze locations on maps (61%).
Tableau insists that its development of new capabilities is guided by customer requests. This provides a source of opportunities to address user needs especially in the areas of data preparation, advanced analytics and location analytics. However, this strategy raises the question of whether it will ultimately put the company in conflict with the partners that have helped build the Tableau ecosystem and feed the momentum of the company thus far. Tableau is positioning its product as a fully featured analytic platform of the sort that I have outlined, but to achieve that eventually it will have to encroach on the capabilities that partners such as Alteryx, Datawatch, Informatica, Lavastorm, Paxata and Trifacta offer today. Another question is whether Tableau will continue its internal development strategy or opt to acquire companies that can broaden its capabilities that has hampered its overall value rating as identified in our 2015 Analytics and Business intelligence Value Index. In light of announcements at the conference, the path seems to be to develop these capabilities in-house. While there appears to be no immediate threat to the partnerships the continuation of development of some of these capabilities eventually will impact the partner business model in a more material way. Given that the majority of the deals for its partner ecosystem flows through Tableau itself, many of the partners are vulnerable to these development efforts. In addition I will be watching how aggressively Tableau helps to market Spark, the open source big data technology that I wrote about, as compared to some of the partner technologies that Spark threatens. Tableau has already built on Spark while some of its competitors have not, which may give Tableau a window of opportunity.
Going forward, integration with transactional systems and emerging cloud ecosystems is an area for Tableau that I will be watching. Given its architecture it's not easy for Tableau to participate in the new generation of service-oriented architectures that characterize part of today's cloud marketplace. For this reason, Tableau will need to continue to build out its own platform and the momentum of its ecosystem – which at this point does not appear to be a problem.
Finally, it will be interesting to see how Tableau eventually aligns its stand-alone data visualization application Vizable with its broader mobile strategy. We will be looking closely at the mobile market in our upcoming Mobile Analytics and Business Intelligence Value Index in the first half of 2016 where in our last analysis found Tableau was in the middle of the pack with other providers but they have made more investments since our last analysis.
We recommend that companies exploring analytics platforms, especially for on-premises and hosted cloud use, include Tableau on their short lists. Organizations that consider deploying Tableau on an enterprise basis should look closely at how it aligns with their broader user requirements and if their cloud strategy will meet its future needs. Furthermore, while the company has made improvements in manageability and performance, these can still be a concern in some circumstances. Tableau should be evaluated also with specific business objectives in mind and in conjunction with its partner ecosystem.
Ventana Research
PentahoWorld 2015, Pentaho's second annual user conference, held in mid-October, centered on the general availability of release 6.0 of its data integration and analytics platform and its acquisition by Hitachi Data Systems (HDS) earlier this year. Company spokespeople detailed the development of the product in relation to the roadmap laid out in 2014 and outlined plans for its integration with those of HDS and its parent Hitachi. They also discussed Pentaho's and HDS's shared intentions regarding the Internet of Things (IoT), particularly in telecommunications, healthcare, public infrastructure and IT analytics.
Pentaho competes on the basis of what it calls a "streamlined data refinery" that enables a flexible way to access, transform and integrate data and embed and present analytic data sets in usable formats without writing new code. In addition, it integrates a visual analytic workflow interface with a business intelligence front end including customization extensions; this is a differentiator for the company since much of the self-serve analytics market in which it competes is still dominated by separate point products.
Pentaho 6 aims to provide manageable and scalable self-service analytics. A key advance in the new version is what Pentaho calls "virtualized data sets" that logically aggregate multiple data sets according to transformations and integration specified by the Pentaho Data Integration (PDI) analytic workflow interface. This virtual approach allows the physical processing to be executed close to the data in various systems such as Hadoop or an RDBMS, which relieves users of the burden of having to continually move data back and forth between the query and the response systems. In this way, logical data sets can be served up for consumption in Pentaho Analytics as well as other front-end interfaces in a timely and flexible manner.
One challenge that emerges when accessing multiple integrated and transformed data sets is data lineage. Tracking its lineage is important to establish trust in the data among users by enabling them to ascertain the origin of data prior to transformation and integration. This is particularly useful in regulated industries that may need access to and tracking of source data to prove compliance. This becomes even more complicated with events and completely sourcing them along with the large number of them as found in over a third of organizations in our operational intelligence benchmark research that examined operational centric analytics and business intelligence.
Similarly, Pentaho 6 uses Simple Network Management Protocol (SNMP) to deliver application programming interface (API) extensions so that third-party tools can help provide governance lower in the system stack to further enable reliability of data. Our benchmark research consistently shows that manageability of systems is important for user organizations and in particular for big data environments.
The flexibility introduced with virtual tables and improvements in Pentaho 6.0 around in-line modeling (a concept I discussed after last year's event are two critical means to building self-service analytic environments. Marrying various data systems with different data models, sometimes referred to as big data integration, has proven to be a difficult challenge in such environments. Pentaho's continued focus on big data integration and providing an integration backbone to the many business intelligence tools (in addition to its own) are potential competitive differentiators for the company. While analysts and users prefer integrated tool sets, today's fragmented analytics market is increasingly dominated by separate tools that prepare data and surface data for consumption. Front-end tools alone cannot automate the big data integration process, which Pentaho PDI can do.Our research into big data integration shows the importance of eliminating manual tasks in this process: 78 percent of companies said it is important or very important to automate their big data integration processes. Pentaho's ability to integrate with multiple visual analytics tools is important for the company, especially in light of the HDS accounts, which likely have a variety of front-end tools. In addition, the ability to provide an integrated front end can be attractive to independent software vendors, analytics services providers and certain end-user organizations that would like to embed both integration and visualization without having to license multiple products.
Going forward, Pentaho is focused on joint opportunities with HDS such as the emerging Internet of Things. Pentaho cites established industrial customers such as Halliburton, Intelligent Mechatonic Systems and Kirchoff Datensysteme Software as reference accounts for IoT. In addition, a conference participant from Caterpillar Marine Asset Intelligence shared how it embeds Pentaho to help analyze and predict equipment failure on maritime equipment. Pentaho's ability to integrate and analyze multiple data sources is key to delivering business value in each of these environments, but the company also possesses a little-known asset in the Weka machine learning library, which is an integrated part of the product suite. Our research on next-generation predictive analytics finds that Weka is used by 5 percent of organizations, and many of the companies that use it are large or very large, which is Pentaho's target market. Given the importance of machine learning in the IoT category, it will be interesting to see how Pentaho leverages this asset.
Also at the conference, an HDS spokesperson discussed its target markets for IoT or what the company calls "social innovation." These markets include telecommunications, healthcare, public infrastructure and IT analytics and reflect HDS's customer base and the core businesses of its parent company Hitachi. Pentaho Data Integration is currently embedded within major customer environments such as Caterpillar, CERN, FINRA, Halliburton, NASDAQ, Sears and Staples, but not all of these companies fit directly into the IoT segments HDS outlined. While Hitachi's core businesses provide a fertile ground in which grow its business, Pentaho will need to develop integration with the large industrial control systems already in place in those organizations.
The integration of Pentaho into HDS is a key priority. The 2,000-strong global sales force of HDS is now incented to sell Pentaho, and it will be important for the reps to include it as they discuss their accounts' needs. While Pentaho's portfolio can potentially broaden sales opportunities for HDS, big data software is a more consultative sale than the price-driven hardware and systems that the sales force may be used to. Furthermore, the buying centers, which are shifting from IT to lines of business, can be significantly different based on the type of organization and their objectives. To address this will require significant training within the HDS sales force and with partner consulting channels. The joint sales efforts will be well served by emphasizing the "big data blueprints" developed by Pentaho over the last couple of years and developing of new ones that speak to IoT and the combined capabilities of the two companies.
HDS says it will begin to embed Pentaho into its product portfolio but has promised to leave Pentaho's roadmap intact. This is important because Pentaho has done a good job of listening to its customers and addressing the complexities that exist in big data and open source environments. As the next chapter unfolds, I will be looking at how the company integrates its platform with the HDS portfolio and expands it to deal with the complexities of IoT, which we will be investigating in upcoming benchmark research study.
For organizations that need to use large-scale integrated data sets, Pentaho provides one of the most flexible yet mature tools in the market, and they should consider it. The analytics tool provides an integrated and embeddable front end that should be of particular interest to analytics services providers and independent software vendors seeking to make information management and data analytics core capabilities. For existing HDS customers, the Pentaho portfolio will open conversations in new areas of those organizations and potentially add considerable value within accounts.
Ventana Research
The emerging Internet of Things (IoT) extends digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere. This innovation enables devices designed for it to generate and transmit data about their operations; analytics using this data can facilitate monitoring and a range of automatic functions.
To perform these functions IoT requires what Ventana Research calls Operational Intelligence (OI), a discipline that has evolved from the capture and analysis of instrumentation, networking and machine-to-machine interactions of many types. We define operational intelligence as a set of event-centered information and analytic processes operating across an organization that enable people to use that event information to take effective actions and make optimal decisions. Our benchmark research into Operational Intelligence shows that organizations most often want to use such event-centric architectures for defining metrics (37%) and assigning thresholds for alerts (35%) and for more action-oriented processes of sending notifications to users (33%) and linking events to activities (27%).
In many industries, organizations can gain competitive advantage if they can reduce the elapsed time between an event occurring and actions taken or decisions made in response to it. Existing business intelligence (BI) tools provide useful analysis of and reporting on data drawn from previously recorded transactions, but to improve competitiveness and maximize efficiencies organizations are concluding that employees and processes – in IT, business operations and front-line customer sales, service and support – also need to be able to detect and respond to events as they happen. Our research into big data integration shows that nearly one in four companies currently integrate data into big data stores in real time. The challenge is to go further and act upon both the data that is stored and the data that is streaming in a timely manner.
The evolution of operational intelligence, especially in conjunction with IoT, is encouraging companies to revisit their priorities and spending for information technology and application management. However, sorting out the range of options poses a challenge for both business and IT leaders. Some see potential value in expanding their network infrastructure to support OI. Others are implementing event processing (EP) systems that employ new technology to detect meaningful patterns, anomalies and relationships among events. Increasingly, organizations are using dashboards, visualization and modeling to notify nontechnical people of events and enable them to understand their significance and take appropriate and immediate action.
As with any innovation, using OI for IoT may require substantial changes. These are among the challenges organizations face as they consider adopting operational intelligence:
- They find it difficult to evaluate the business value of enabling real-time sensing of data and event streams using identification tags, agents and other systems embedded not only in physical locations like warehouses but also in business processes, networks, mobile devices, data appliances and other technologies.
- They lack an IT architecture that can support and integrate these systems as the volume and frequency of information increase.
- They are uncertain how to set reasonable business and IT expectations, priorities and implementation plans for important technologies that may conflict or overlap. These can include business intelligence, event processing, business process management, rules management, network upgrades and new or modified applications and databases.
- They don't understand how to create a personalized user experience that enables nontechnical employees in different roles to monitor data or event streams, identify significant changes, quickly understand the correlation between events and develop a context in which to determine the right decisions or actions to take.
Ventana Research has announced new benchmark research on The Internet of Things and Operational Intelligence that will identify trends and best practices associated with this technology and these processes. It will explore organizations' experiences with initiatives related to events and data and with attempts to align IT projects, resources and spending with new business objectives that demand real-time intelligence and event-driven architectures. The research will investigate how organizations are increasing their responsiveness to events by rebalancing the roles of networks, applications and databases to reduce latency; it also will explore ways in which they are using sensor data and alerts to anticipate problematic events. We will benchmark the performance of organizations' implementations, including IoT, event stream processing, event and activity monitoring, alerting, event modeling and workflow, and process and rules management.
As operational intelligence evolves as the core of IoT platforms, it is an important time to take a closer look at this emerging opportunity and challenge. For those interested in learning more or becoming involved in this upcoming research, please let me know.
Ventana Research
Splunk's annual gathering, this year called .conf 2015, in late September hosted almost 4,000 Splunk customers, partners and employees. It is one of the fastest-growing user conferences in the technology industry. The area dedicated to Splunk partners has grown from a handful of booths a few years ago to a vast showroom floor many times larger. While the conference's main announcement was the release of Splunk Enterprise 6.3, its flagship platform, the progress the company is making in the related areas of machine learning and the Internet of Things (IoT) most caught my attention.
Splunk's strength is its ability to index, normalize, correlate and query data throughout the technology stack, including applications, servers, networks and sensors. It uses distributed search that enables correlation and analysis of events across local- and wide-area networks without moving vast amounts of data. Its architectural approach unifies cloud and on-premises implementations and provides extensibility for developers building applications. Originally, Splunk provided an innovative way to troubleshoot complex technology issues, but over time new uses for Splunk-based data have emerged, including digital marketing analytics, cyber security, fraud prevention and connecting digital devices in the emerging Internet of Things. Ventana Research has covered Splunk since its establishment in the market, most recently in this analysis of mine.
Splunk's experience in dealing directly with distributed, time-series data and processes on a large scale puts it in position to address the Internet of Things from an industrial perspective. This sort of data is at the heart of large-scale industrial control systems, but it often comes in different formats and its implementation is based on different formats and protocols. For instance, sensor technology and control systems that were invented 10 to 20 years ago use very different technology than modern systems. Furthermore, as with computer technology, there are multiple layers in stack models that have to communicate. Splunk's tools help engineers and systems analysts cross-reference these disparate systems in the same way that it queries computer system and network data, however, the systems can be vastly different. To address this challenge, Splunk turns to its partners and its extensible platform. For example, Kepware has developed plug-ins that use its more than 150 communication drivers so users can stream real-time industrial sensor and machine data directly into the Splunk platform. Currently, the primary value drivers for organizations in this field of the industrial IoT are operational efficiency, predictive maintenance and asset management. At the conference, Splunk showcased projects in these areas including one with Target that uses Splunk to improve operations in robotics and manufacturing.
For its part, Splunk is taking a multipronged approach by acquiring companies, investing in internal development and enabling its partner ecosystem to build new products. One key enabler of its approach to IoT is machine learning algorithms built on the Splunk platform. In machine learning a model can use new data to continuously learn and adapt its answers to queries. This differs from conventional predictive analytics, in which users build models and validate them based on a particular sample; the model does not adapt over time. With machine learning, for instance, if a piece of equipment or an automobile shows a certain optimal pattern of operation over time, an algorithm can identify that pattern and build a model for how that system should behave. When the equipment begins to act in a less optimal or anomalous way, the system can alert a human operator that there may be a problem, or in a machine-to-machine situation, it can invoke a process to solve the problem or recalibrate the machine.
Machine learning algorithms allow event processes to be audited, analyzed and acted upon in real time. They enable predictive capabilities for maintenance, transportation and logistics, and asset management and can also be applied in more people-oriented domains such as fraud prevention, security, business process improvement, and digital products. IoT potentially can have a major impact on business processes, but only if organizations can realign systems to discover-and-adapt rather than model-and-apply approaches. For instance, processes are often carried out in an uneven fashion different from the way the model was conceived and communicated through complex process documentation and systems. As more process flows are directly instrumented and more processes carried out by machines, the ability to model directly based on the discovery of those event flows and to adapt to them (through human learning or machine learning) becomes key to improving organizational processes. Such realignment of business processes, however, often involves broad organizational transformation.Our benchmark research on operational intelligence shows that challenges associated with people and processes, rather than information and technology, most often hold back organizational improvement.
Two product announcements made at the conference illuminate the direction Splunk is taking with IoT and machine learning. The first is User Behavior Analytics (UBA), based on its acquisition of Caspida, which produces advanced algorithms that can detect anomalous behavior within a network. Such algorithms can model internal user behavior, and when behavior deviates from the specified norm, it can generate an alert that can be addressed through investigative processes usingSplunk Enterprise Security 4.0. Together, Splunk Enterprise Security 4.0 and UBA won the 2015 Ventana Research CIO Innovation Award.The acquisition of Caspida shows that Splunk is not afraid to acquire companies in niche areas where they can exploit their platform to deliver organizational value. I expect that we will see more such acquisitions of companies with high value ML algorithms as Splunk carves out specific positions in the emergent markets.
The other product announced is IT Service Intelligence (ITSI), which highlights machine learning algorithms alongside of Splunk's core capabilities. The IT Service Intelligence App is an application in which end users deploy machine learning to see patterns in various IT service scenarios. ITSI can inform and enable multiple business uses such as predictive maintenance, churn analysis, service level agreements and chargebacks. Similar to UBA, it uses anomaly detection to point out issues and enables managers to view highly distributed processes such as claims process data in insurance companies. At this point, however, use of ITSI (like other areas of IoT) may encounter cultural and political issues as organizations deal with changes in the roles of IT and operations management. Splunk's direction with ITSI shows that the company is staying close to its IT operations knitting as it builds out application software, but such development also puts Splunk into new competitive scenarios where legacy technology and processes may still be considered good enough.
We note that ITSI is built using Splunk's Machine Learning Toolkit and showcase, which currently is in preview mode. The platform is an important development for the company and fills one of the gaps that I pointed out in its portfolio last year. Addressing this gap enables Splunk and its partners to create services that apply advanced analytics to big data that almost half (45%) of organizations find important. The use of predictive and advanced analytics on big data I consider a killer application for big data; our benchmark research on big data analytics backs this claim: Predictive analytics is the type of analytics most (64%) organizations wish to pursue on big data.
Organizations currently looking at IoT use cases should consider Splunk's strategy and tools in the context of specific problems they need to address. Machine learning algorithms built for particular industries are key so it is important to understand if the problem can be addressed using prebuilt applications provided by Splunk or one of its partners, or if the organization will need to build its own algorithms using the Splunk machine learning platform or alternatives. Evaluate both the platform capabilities and the instrumentation, the type of protocols and formats involved and how that data will be consumed into the system and related in a uniform manner. Most of all, be sure the skills and processes in the organization align with the technology from an end user and business perspective.
Ventana Research
The concept and implementation of what is called big data are no longer new, and many organizations, especially larger ones, view it as a way to manage and understand the flood of data they receive. Our benchmark research on big data analytics shows that business intelligence (BI) is the most common type of system to which organizations deliver big data. However, BI systems aren't a good fit for analyzing big data. They were built to provide interactive analysis of structured data sources using Structured Query Language (SQL). Big data includes large volumes of data that does not fit into rows and columns, such as sensor data, text data and Web log data. Such data must be transformed and modeled before it can fit into paradigms such as SQL.
The result is that currently many organizations run separate systems for big data and business intelligence. On one system, conventional BI tools as well as new visual discovery tools act on structured data sources to do fast interactive analysis. In this area analytic databases can use column store approaches and visualization tools as a front end for fast interaction with the data. On other systems, big data is stored in distributed systems such as the Hadoop Distributed File System (HDFS). Tools that use it have been developed to access, process and analyze the data. Commercial distribution companies aligned with the open source Apache Foundation, such as Cloudera, Hortonworks and MapR, have built ecosystems around the MapReduce processing paradigm. MapReduce works well for search-based tasks but not so well for the interactive analytics for which business intelligence systems are known. This situation has created a divide between business technology users, who gravitate to visual discovery tools that provide easily accessible and interactive data exploration, and more technically skilled users of big data tools that require sophisticated access paradigms and elongated query cycles to explore data.
There are two challenges with the MapReduce approach. First, working with it is a highly technical endeavor that requires advanced skills. Our big data analytics research shows that lack of skills is the most widespread reason for dissatisfaction with big data analytics, mentioned by more than two-thirds of companies. To fill this gap, vendors of big data technologies should facilitate use of familiar interfaces including query interfaces and programming language interfaces. For example, our research shows that Standard SQL is the most important method for implementing analysis on Hadoop. To deal with this challenge, the distribution companies and others offer SQL abstraction layers on top of HDFS, such as HIVE and Cloudera Impala. Companies that I have written about include Datameer and Platfora, whose systems help users interact with Hadoop data via interactive systems such as spreadsheets and multidimensional cubes. With their familiar interaction paradigms such systems have helped increase adoption of Hadoop and enable more than a few experts to access big data systems.
The second challenge is latency. As a batch process MapReduce must sort and aggregate all of the data before creating analytic output. Technology such as Tez, developed by Hortonworks, and Cloudera Impala aim to address such speed limitations; the first leverages MapReduce, and the other circumvents MapReduce altogether. Adoption of these tools has moved the big data market forward, but challenges remain such as the continuing fragmentation of the Hadoop ecosystem and a lack of standardization in approaches.
An emerging technology holds promise for bridging the gap between big data and BI in a way that can unify big data ecosystems rather than dividing them. Apache Spark, under development since 2010 at the University of California Berkeley's AMPLab, addresses both usability and performance concerns for big data. It adds flexibility by running on multiple platforms in terms of both clustering (such as Hadoop YARN and Apache Mesos) and distributed storage (for example, HDFS, Cassandra, Amazon S3 and OpenStack's Swift). Spark also expands the potential uses because the platform includes an SQL abstraction layer (Spark SQL), a machine learning library (MLlib), a graph library (GraphX) and a near-real-time engine (Spark Streaming). Furthermore, Spark can be programmed using modern languages such as Python and Scala. Having all of these components integrated is important because interactive business intelligence, advanced analytics and operational intelligence on big data all can work without dealing with the complexity of having individual proprietary systems that were necessary to do the same things previously.
Because of this potential Spark is becoming a rallying point for providers of big data analytics. It has become the most active Apache project as key open source contributors moved their focus from other Hadoop projects to it. Out of the effort in Berkeley, Databricks was founded for commercial development of open source Apache Spark and has raised more than $46 million. Since the initial release in May 2014 the momentum for Spark has continued to build; major companies have made announcements around Apache Spark. IBM said it will dedicate 3,500 researchers and engineers to develop the platform and help customers deploy it. This is the largest dedicated Spark effort in the industry, akin to the move IBM made in the late 1990s with the Linux open source operating system. Oracle has built Spark into its Big Data Appliance. Microsoft has Spark as an option on its HDInsight big data approach but has also announced Prajna, an alternative approach to Spark. SAP has announced integration with its SAP HANA platform, although it represents "coopetition" for SAP's in-memory platform. In addition, all the major business intelligence players have built or are building connectors to run on Spark. In time, Spark likely will serve as a data ingestion engine for connecting devices in the Internet of Things (IoT). For instance, Spark can integrate with technologies such as Apache Kafka or Amazon Kinesis to instantly process and analyze IoT data so that immediate action can be taken. In this way, as it is envisioned by its creators, Spark can serve as the nexus of multiple systems.
Because it is a flexible in-memory technology for big data, Spark opens the door to many new opportunities, which in business use include interactive analysis, advanced customer analytics,fraud detection, and systems and network management. At the same time, it is not yet a mature technology and for this reason, organizations considering adoption should tread carefully. While Spark may offer better performance and usability, MapReduce is already widely deployed. For those users, it is likely best to maintain the current approach and not fix what is not broken. For future big data use, however, Spark should be carefully compared to other big data technologies. In this case as well as others, technical skills can still be a concern. Scala, for instance, one of the key languages used with Spark, has little adoption, according to our recent research on next-generation predictive analytics. Manageability is an issue as for any other nascent technology and should be carefully addressed up front. While, as noted, vendor support for Spark is becoming apparent, frequent updates to the platform can mean disruption to systems and processes, so examine the processes for these updates. Be sure that vendor support is tied to meaningful business objectives and outcomes. Spark is an exciting new technology, and for early adopters that wish to move forward with it today, both big opportunities and challenges are in store.
Ventana Research
As I discussed in the state of data and analytics in the cloud recently, usability is a top evaluation criterion for organizations in selecting cloud-based analytics software. Data access of cloud and on-premises systems are essential antecedents of usability. They can help business people perform analytic tasks themselves without having to rely on IT. Some tools allow data integration by business users on an ad hoc basis, but to provide an enterprise integration process and a governed information platform, IT involvement is often necessary. Once that is done, though, using cloud-based data for analytics can help, empowering business users and improving communication and process .
To be able to make the best decisions, organizations need access to multiple integrated data sources. The research finds that the most common data sources are predictable: business applications (51%), business intelligence applications (51%), data warehouses or operational data stores (50%), relational databases (41%) and flat files (33%). Increasingly, though, organizations also are including less structured sources such as semistructured documents (33%), social media (27%) and nonrelational database systems (19%). In addition there are important external data sources, including business applications (for 61%), social media data (48%), Internet information (42%), government sources (33%) and market data (29%). Whether stored in the cloud or locally, data must be normalized and combined into a single data set so that analytics can be performed.
Given the distributed nature of data sources as well as the diversity of data types, information platforms and integration approaches are changing. While more than three in five companies (61%) still do integration primarily between on-premises systems, significant percentages are now doing integration from the cloud to on-premises (47%) and from on-premises to the cloud (39%). In the future, this trend will become more pronounced. According to our research, 85 percent of companies eventually will integrate cloud data with on-premises sources, and 84 percent will do the reverse. We expect that hybrid architectures, a mix of on-premises and cloud data infrastructures, will prevail in enterprise information architectures for years to come while slowly evolving to equality of bidirectional data transfer between the two types.
Further analysis shows that a focus on integrating data for cloud analytics can give organizations competitive advantage. Those who said it is very important to integrate data for cloud-based analytics (42% of participants) also said they are very confident in their ability to use the cloud for analytics (35%); that's three times more often than those who said integrating data is important (10%) or somewhat important (9%). Those saying that integration is very important also said more often that cloud-based analytics helps their customers, partners and employees in an array of ways, including improved presentation of data and analytics (62% vs. 43% of those who said integration is important or somewhat important), gaining access to many different data sources (57% vs. 49%) and improved data quality and data management (59% vs. 53%). These numbers indicate that organizations that neglect the integration aspects of cloud analytics are likely to be at a disadvantage compared to their peers that make it a priority.
Integration for cloud analytics is typically a manual task. In particular, almost half (49%) of organizations in the research use spreadsheets to manage the integration and preparation of cloud-based data. Yet doing so poses serious challenges: 58 percent of those using spreadsheets said it hampers their ability to manage processes efficiently. While traditional methods may suffice for integrating relatively small and well-defined data sets in an on-premises environment, they have limits when dealing with the scale and complexity of cloud-based data. The research also finds that organizations utilizing newer integration tools are satisfied with them more often than those using older tools. More than three-fourths (78%) of those using tools provided by a cloud applications provider said they are satisfied or somewhat satisfied with them, as are even more (86%) of those using data integration tools designed for cloud computing; by comparison, fewer of those using spreadsheets (56%) or traditional enterprise data integration tools (71%) are satisfied.
This is not surprising. Modern cloud connectors are designed to connect via loosely coupled interfaces that allow cloud systems to share data in a flexible manner. The research thus suggests that for organizations needing to integrate data from cloud-based data sources, switching to modern integration tools can streamline the process.
Overall three-quarters of companies in our research said that it is important or very important to access data from cloud-based sources for analysis. Cloud-based analytics isn't useful unless the right data can be fed into the analytic process. But without capable tools this is not easy to do. A substantial impediment is that analysts spend the majority of their time in accessing and preparing the data rather than in actual analysis. Complicating the task, each data source can represent a different, possibly complex, data model. Furthermore, the data sets may have varying data formats and interface requirements, which are not easily addressed with legacy integration tools.
Such complexity is the new reality, and new tools and approaches have come to market to address these complexities. For organizations looking to integrate their data for cloud-based analytics, we recommend exploring these new integration processes and technologies.
Ventana Research
Our recently completed benchmark research on data and analytics in the cloud shows that analytics deployed in cloud-based systems is gaining widespread adoption. Almost half (48%) of participating organizations are using cloud-based analytics, another 19 percent said they plan to begin using it within 12 months, and 31 percent said they will begin to use cloud-based analytics but do not know when. Participants in various areas of the organization said they use cloud-based analytics, but front-office functions such as marketing and sales rated it important more often than did finance, accounting and human resources. This front-office focus is underscored by the finding that the categories of information for which cloud-based analytics is most often deemed important are forecasting (mentioned by 51%) and customer-related (47%) and sales-related (33%) information.
The research also shows that while adoption is high, organizations face challenges as they seek to realize full value from their cloud-based data and analytics initiatives. Our Performance Index analysis reveals that only one in seven organizations reach the highest Innovative level of the four levels of performance in their use of cloud-based analytics. Of the four dimensions we use to further analyze performance, organizations do better in Technology and Process than in Information and People. That is, the tools and analytic processes used for data and analytics in the cloud have advanced more rapidly than users' abilities to work with their information. The weaker performance in People and Information is reflected in findings on the most common barriers to deployment of cloud-based analytics: lack of confidence about the security of data and analytics, mentioned by 56 percent of organizations, and not enough skills to use cloud-based analytics (42%).
Given the top barrier of perceived data security issues, it is not surprising the research finds that the largest percentage of organizations (66%) use a private cloud, which by its nature ostensibly is more secure, to deploy analytics; fewer use a public cloud (38%) or a hybrid cloud (30%), although many use more than one type today. We know from tracking analytics and business intelligence software providers that operate in the public cloud that this is changing quite rapidly. Comparing deployment by industry sector, the research analysis shows that private and hybrid clouds are more prevalent in the regulated areas of finance, insurance and real estate and government than in services and manufacturing. The research suggests that private and hybrid cloud deployments are used more often for analytics where data privacy is a concern.
Furthermore, organizations said that access to data for analytics is easier with private and hybrid clouds (29% for public cloud vs. 58% for private cloud and 67% for hybrid cloud). In addition, organizations using private and hybrid cloud more often said they have improved communication and information sharing (56% public vs. 72% private and 70% hybrid). Thus, the research data makes clear that organizations feel more comfortable implementing analytics in a private or hybrid cloud in many areas.
Private and hybrid cloud implementations of data and analytics often coincide with large data integration efforts, which are necessary at some point to benefit from such deployments. Those who said that integration is very important also said more often than those giving it less importance that cloud-based analytics helps their customers, partners and employees in an array of ways, including improved presentation of data and analytics (62% vs. 43% of those who said integration is important or somewhat important), gaining access to many different data sources (57% vs. 49%) and improved data quality and data management (59% vs. 53%). We note that the focus on data integration efforts correlates more with private and hybrid cloud approaches than with public cloud approaches, thus the benefits cannot be directly assigned to the various cloud approaches nor the integration efforts.
Another key insight from the research is that data and analytics often are considered in conjunction with mobile and collaboration initiatives which have different priorities for business than IT or in consumer markets. Nine out of 10 organizations said they use or intend to use collaboration technology to support their cloud-based data and analytics, and 83 percent said they need to support data access and analytics on mobile devices. Two-thirds said they support both tablets and smartphones and multiple mobile operating systems, the most important of which are Apple iOS (ranked first by 60%), Google Android (ranked first by 26%) and Microsoft Windows Mobile (ranked first by 13%). We note that Microsoft has a higher percentage of importance here than its reported market share (approximately 2.5%) would suggest. Similarly, Google Android has greater penetration than Apple in the consumer market (51% vs. 41%). We expect that the influence of mobile operating systems related to data and analytics in the cloud will continue to evolve and be impacted by upcoming corporate technology refreshment cycles, the consolidation of PCs and mobile devices, and the "bring your own device" (BYOD) trend.
The research finds that usability (63%) and reliability (57%) are the top technology buying criteria, which is consistent with our business technology innovation research conducted last year. What has changed is that manageability is cited as very important as often as functionality, by approximately half of respondents, a stronger showing than in our previous research. We think it likely that manageability is gaining prominence as cloud providers and organizations sort out issues in who manages deployments along with usage and licensing, along with who actually owns your data in the cloud which my colleague Robert Kugel has discussed.
As the research shows, the importance of cloud data and analytics is continuing to grow. The importance of this topic makes me eager to discuss further the attitudes, requirements and future plans of organizations that use data and analytics in the cloud and to identify the best practices of those that are most proficient in it. For more information on this topic, and learn more on best practices for data and analytics in the cloud, and download the executive summary of the report to improve your readiness.
Ventana Research


text:
ChessJam is a beautiful new online chess game powered by Adobe AIR that allows users to play chess with others from around the world. Greg Wilson, one of the developers of the application and an Adobe employee, wrote a detailed blog post on how the application was created using Flex, Adobe AIR, ColdFusion and LiveCycle DS.
When asked why the team that developed this application chose Adobe AIR, Greg responded with the following points:
- Embedded images and sounds dramatically speed-up load times compared to an equivalent web-browser-based app
- User presence detection
- Network detection for handling disconnects and reconnects
- Custom chrome (the team wanted 100% control over UI, sizing, position, etc.)
- Numerous uses of mx:HTML including the news banner, upcoming stats view, etc.
- Auto-update framework to easily push out updates to the application.
- Support for Mac, Windows and Linux
Greg mentioned that there are plans to release other features that take advantage of AIR soon including toast-style notifications, local game history storage using the SQLite database and more. Congratulations to the ChessJam for building a fabulous game.