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Coconut Cream Pie II
Ingredients7 h servings 500
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- Metric
Directions{{model.addEditText}} Print
- Preheat oven to 350 degrees F (175 degrees C).
- In a medium bowl, mix together wafer crumbs and melted butter. Press mixture firmly into bottom and sides of a 9-inch pie pan. Bake in preheated oven for 7 minutes. Remove and allow to cool.
- Dissolve gelatin in cold milk and set aside to soften.
- Beat egg yolks and sugar together, then slowly pour in hot milk while whisking constantly. Cook over medium heat, stirring constantly, until mixture coats a spoon. Remove from heat, then stir in gelatin, followed by almond extract. Chill.
- Beat egg whites until stiff. Fold egg whites, whipped cream, and coconut into chilled custard. Pour into pie shell, and sprinkle with additional coconut. Chill 6 hours or overnight before serving.
Nutrition Facts
Per Serving: 500 calories; 32.9 46.1 7.1 141 214 Full nutrition
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ReviewsRead all reviews 10
14 Ratings
I made this pie for Christmas and it was the first pie that was gone. My family loved it! I made a regular pie crust and it was very good. I was surpised to find that I had enough mix to make...
it was ok
I made this pie for Christmas and it was the first pie that was gone. My family loved it! I made a regular pie crust and it was very good. I was surpised to find that I had enough mix to make...
This pie is delicious. The two Coconut Cream Pie lovers absolutely fell in lov. I guess I have to make it all the time now!
The recipe turned out great. I made a homemade crust to go with it instead of the graham-cracker crust and it tastes great. Next time, though, I think I will cut way back on the almond flavor. I...
Delicious pie!! So good. Creamy, fluffy and coconutty. I have also made it with a chocolate cookie crumb crust and drizzled a chocolate ganache on top. A great treat for the chocolate coconut lo...
This pie was really good! Thanks for sharing your recipe with us, on allrecipes.com!
Made this for Thanksgiving Dinner - a wonderful addition to the dinner. I will make it again. Love the vanilla wafer crust. I didn't have any gelatin and used corn starch instead and it work...
it was ok
I made this for Christmas this year and everyone really liked it! I made it with regular pie crust and a little less almond extract. It was very good!


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Buy Game of Thrones Merchandise
Famous Youtuber/Game of Thrones theorist Alt-Shift-X, decided to take a break from fan theories and as an April Fool's day prank, analyzed Thrones porn parody Game of Bones with a straight face. He starts the video with the following introduction:
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We need to provide functionality for our field Sales people to submit monthly expenses for reimbursement. These are day-to-day business expenses like the following: Phone Bills, Mileage, Clerical expenses, Printer cartridges, etc. Each Sales person has a designated limit that they can submit each quarter and each year – based on the size of their Sales territory. So a traditional expense reimbursement package likely won't fit the bill without a good amount of customization.
Has anyone used Dynamics CRM for expense submissions and approvals? Since our Sales people are in CRM on a daily basis, it seems there could be some benefit to having this information in CRM: we could display status information on a dashboard, provide a future Power App, etc. Is this a stretch since outside of the connection to an employee in CRM, there aren't any ties to CRM entities that would necessitate building this functionality into CRM? The alternative we are looking at is a homegrown Web application – with a link to this application from CRM.
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Description: Gemütliche Sitzecke Im Garten Gestalten Einfach 42 Einzigartig Garten Gemütlich Gestalten Stock Foto from the above resolutions which is part of the Gartengestaltung Pflege. Download this image for free in HD resolution the choice "download button" below. If you do not find the exact resolution you are looking for, then go for a native or higher resolution.
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Gemütliche Sitzecke Im Garten Gestalten Einfach 42 Einzigartig Garten Gemütlich Gestalten Stock Foto - You need to garden and terrace ideas for a limited space? The herb spiral is just Right for you! Related to the spiral arrangement they offer the possibility not to have in order to do without having a beautiful garden even with little space. A further advantage are the different levels-so you can even plant herbs and plants with different location requirements. Depending on where these are housed, different lighting conditions prevail. Mediterranean herbs similar as rosemary grow in the upper, nutrient-poor and dry area, while the peppermint on the floor of the herb spiral, a damp and nutrient-rich place.


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I would like more information. I have a 1961 and a 1967 yearbook from TVHSReply
I may be able to attend parts of the event. I will be teaching a workshop in Calgary on Saturday.
As I live in New Westminster, BC, it is just luck that I will be in Longview with my parents at this time. Great timing!
Carol would you be related to Doug? If you went to school there you are more than welcome. The cost is $30.00 per person at the Legion, 6.'clock!
Dead line is July 1st.We also meet at the Hotel for Sunday breakfast you pay your own. We have a couple of raffles also.
Contact me: Joyce Compton Berkholtz
3807 62st
Camrose Ab.T4V 3B5
Phone Nos. Home 1-780-627-1952
Hi Joyce, Yes, I am Dougs' sister. I hope you mean Doug Carter BUT in case you mean Doug Herron, well, then I'm his sister-in-law. Is there any pre-registration for this? If so, where do I send the cheque or how do I register? My sister Joyce McGregor also attended T.V. schools. Doug C. lives in Sherwood Park and Doug Herron lives in Victoria. Younger sister Sherry also attended T.V. High. I would love to hear more, if you have time please reply.Reply
Hi, I was wondering if anyone can help me, my mom, Shirley May Munroe and her sister Joyce lived in Turner Valley and went to the Turner valley school in the late thirties and forties (my mom was born in 1932, her sister in 1936), and I was wondering if anyone had school yearbooks from around this time, or knew them and had pictures? My mom had old school papers etc. but they were misplaced long ago….. anyway, thank you!! 🙂Reply


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No business owner wants to admit that bankruptcy is the best way to resolve unmanageable debt, but for many, that decision ultimately must be made. That creates another decision: what bankruptcy is best for your small business?
How to reduce your small business debt and avoid liquidation
Running your own small business is challenging even when business is good. When your company starts to lose money, running a small business can seem next to impossible. Depending on your business entity, you may also have personal assets tied to the livelihood of your business. Even if your personal property is not liable for business debts, you still have a lot invested in your company.
Chapter 7 bankruptcy: Will I keep my business?
As a small business owner who has insurmountable debt, you are considering the drastic step of filing bankruptcy. You have done some research online, and Chapter 7 seems the best fit for your particular circumstances. Of course, you have many questions. The biggest is this: Will you be able to keep your business after you declare Chapter 7 bankruptcy?
Be sure to take lessons away from a bankruptcy
Think of Chapter 13 bankruptcy as a business mulligan. Some tremendously successful figures in U.S. history have declared bankruptcy, including our current president and the president widely considered to be among the best ever. Abraham Lincoln had to repay creditors over a period of 17 years after a general store he co-owned failed.
Is it getting easier to get business loans?
It appears that a fair number of banks are making it easier for companies to get loans these days. This is what a recent survey by the Federal Reserve suggests.
California leads country in wage theft lawsuits
As an employer, it is your duty to make sure that each of your employees receive fair pay and treatment while ensuring that your company continues to make profits. Unfortunately, many companies in California fail to adhere to these standards and attempt to boost their earnings by forcing their workers to work off the clock without overtime pay.
Out Of Court Reorganziation
I just finished helping a Southern California business wind down its affairs and resolve matters with its creditors without a bankruptcy filing. The creditors did far better than they would have in a bankruptcy. We created a soft landing for the business, its owners and its creditors. Did so using a technique I created and have used multiple times with great success. If your business is having financial challenges, hiring an experienced and creative debt restructing lawyer can make all the difference in the world and save you many sleepless nights.


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In this era, the role of the IT department is much more than keeping the lights on. From machine learning and artificial intelligence (AI) to cybersecurity and customer engagement, technology is reshaping the way we do business.
In this environment, IT is no longer just a means to keep functional areas afloat: It's a primary driver of organizational strategy. At our most recent IEF dinner in Seattle, we spoke with IT executives about having a seat at the table when it comes to the strategic direction in their organizations. Below we share some key insights from those who joined us, with a focus on:
– Leading through change in the face of disruptive forces
– Tapping into data and analytics to create value
– Capturing and communicating the business value of IT
Leading the Charge
Technology is a disruptive force in business and the pace of change is only accelerating. Factors that once put a company ahead no longer has the same staying power.
"We were first-to-market, we were patented with that model. But that's only going to carry us so far," offered one attendee from a pet insurance provider. "For a long time, it was our product that put us over our competitors. A lot of competitors have now copied our product." The member explained that despite being a market leader in the field, his organization could shed market share to a competitor offering a better app-driven experience.
An IEF member in the digital ad space described a major disruptive force in the creative industry: The big consulting firm with the highly repeatable standard process, as opposed to the traditional agency that searches for the "secret sauce" in every account.
These firms offer an efficient, inexpensive and scalable alternative to traditional agency work. For the moment, he explained, this approach will fail to win over major accounts. However, the danger lies in thinking this approach only threatens the business's low-hanging fruit. What was once a fringe competitor in the industry could move to the core as they refine their business model. "The problem is that you stop paying attention. They start creeping up your chain and pretty soon they've eaten your business."
Today, business leaders in every vertical must ask themselves the question, "Could we be disrupted by an app?" The answer is: Yes. Every company is becoming a technology company in some form. Those who aren't will fall behind.
Whether internal or external, this means IT leaders play a bigger role in leading their organizations through transformation. As one attendee lamented, "we're doing a lot of organizational change management we did not imagine we would have to be doing a few years ago."
Nonetheless, change management is now a vital facet of IT leadership. As more business outcomes become dependent on technology, it falls to IT departments to plan, implement and drive adoption of new tools. From refreshing office technology through what one attendee dubbed "ax the fax" programs to transitioning out of the data center business, the organization counts on IT to transform the way work gets done, break down silos and drive a better digital experience.
A representative of the financial services sector saw the value in bringing a streamlined digital experience to customers. She also weighed in on the associated challenges:
"When users go to Uber, they get an experience that's really good. Every week, their expectations are rising, and we need to be able to meet those, to make their lives a little easier."
Further Reading: 1 Reason Why Most Change Management Efforts Fail (Forbes)
Data: Fuel for Disruption
In October, Dell EMC announced a massive $1B R&D investment in the Internet of Things (IoT). The move signals the company's push behind edge computing. It also recognizes the enormous potential for data to power disruption.
As organizations harvest more data through technology products, services, and devices, IT leaders play a greater role in harvesting this rich intelligence. The question is, as one attendee explained, "How do we take information that's available to us and turn it into meaningful insights?"
Many modern technology products capture data on almost all aspects of their usage. Many also have artificial intelligence (AI) components that analyze the resulting data to spot trend indicators and drive value. These analytics create outstanding opportunities to improve engagement with customers and open new revenue streams for the company.
Often, that data is critical to driving product decisions, or steering marketing and advertising strategies. In fact, sometimes this data holds more value than the initial transaction itself.
One member in digital advertising gave the example of a movie rental kiosk company. They discovered, "The DVD was not the market. It was the person renting the DVD."
He explained that capturing the transaction data and tying it back to the retail location where the rental took place empowered the kiosk operator with much richer information about the customer. This, in turn, fueled better-targeted marketing and promotional efforts across several touch points.
"We're trying to determine who's using our product and what features they're using: How does that help us sell more product, not just build it."
As one attendee representing a network of specialty surgeons indicated, his organization gathers and analyzes patient outcome data to articulate their value to patients as well as their referral network of primary physicians.
"Analytics is key for us. In a very competitive world, that's our leverage. That's our advantage."
Further Reading: The Edge Will Eat the Cloud (Gartner)
Building the IT Value Prop
Technology is no longer seen as the purview of one specialized function area. It now permeates every aspect of the business. In a scenario where technology is integrated with every line of business, IT leaders often feel the need to re-evaluate the ways their department adds value and re-invent the ways they communicate that value.
As one IEF member stated, "While we've always worked very hard to keep the lights on and keep our data centers enabled, there's always been a solution focus to our team."
"It always comes back to the mantra of 'Business value of IT.'"
One member described implementing best-in-breed solutions and driving adoption of machine learning and AI tools to strengthen his team's value to the business. The result was a dramatic improvement in the real-time delivery of critical reports.
Another member in the workflow automation sector gave the example of adapting his own company's products to provide an in-house solution for their customer portal. This success enabled his IT department to play a principal role in shaping and defining the customer experience. It also provided an excellent case study to take to clients.
"We've been able to improve the way [our company] does business with [our company's] products. It was an amazing opportunity to sweep in and develop a custom solution."
This question of IT's business value is perhaps felt strongest around the subject of cybersecurity investments. "There hasn't been a meeting I've been in where someone didn't say this was a top concern for him or her," said Alayna Broderson, the District Sales Director from Softchoice.
In any industry, data security is paramount. In some verticals, the cost of a breach is beyond extensive. "You cannot afford to spend at a level where you're 100% secure," complained one attendee. "There's no such thing as 100% secure," argued another.
While the best time to go to the business for more investment may appear to be after an incident, one member offers an alternative approach: When no incident occurs, remind the business that security investment pays off. "Remember all that money I asked you for two years ago? That's why we didn't have an impact. That kept us in business."
At the end of the day, accountability for security rises to the top: "Our role within technology is to make sure executives understand that this is a business decision, not an IT decision."
Further Reading: IT's Future Value Proposition (McKinsey)
Last Thoughts
This concludes our IEF Seattle event, where we learned more about the evolving role of IT leadership in maintaining the agility and security of the organization. Here are the key takeaways:
– No organization or industry is safe from disruptive technology, but IT is poised to lead change
– Data drives pivotal product intelligence and IT holds the keys
– A disruptive environment strengthens the IT department's value proposition
– Security is not a single department accountability
Have any thoughts to add? Join the conversation. #CIOTableTalk


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Isoke Salaam is an East Coast PR girl originally from New Jersey with private clients within fashion and the arts. When not reviewing a client portfolio, typing on an iPad and answering her cell phone while balancing in heels, Isoke practices ballet, enjoys running, writing, reading, traveling and learning about art! She is a PR powerhouse, an avid art fan and a fashion lover.
I met Isoke when I became an advocate for the D.C. Humane Rescue Alliance and the 2017 Fashion for Paws event. I was instantly drawn to her because of her grace, her grit, and the way she exudes a certain calm, and connectedness that is so rare in busy, professional types these days! After getting to know her, I learned that she cultivates this through a daily gratitude practice (along with a lifetime of being an exceptional human!).
Isoke lives a very dynamic, jet-setting life. She is a true individual, with a very freely-chosen definition of success, and so much authenticity. It's been a pleasure getting to know her, and developing a friendship with her. In our interview, we cover fashion, fitness, travel, self-care, and of course, a daily practice of cultivating gratitude! We can all learn something from Isoke and the fabulous life she's created for herself!
Key takeaways:
● Isoke's life as a PR maven in Washington, D.C. working with clients worldwide
● How Isoke shows her body love through movement, and her love of boutique fitness
● Being a "non-judgy" vegetarian
● Isoke's adult gap year living in Paris and how she made that happen
● What it's like being a tall, striking, woman of color and a professional
● Isoke's daily spiritual practice, including her gratitude practice
● The legacy that Isoke is working to create for herself (hint: it's not marriage and kids)
● The jet setting life Isoke leads, and all the countries she's visited this year
● The importance of creating financial freedom, and how Isoke did this for herself
● Life lists and how to use them to create a dream experience!
Mentioned in this episode:
Isoke's Daily Gratitude Practice
Isoke's PR business
Isoke's client, Cija, and her new book
Share the Body Love!
Share what you learned here via Facebook, Instagram, Pinterest, or Twitter
Subscribe on iTunes and leave a review. I love hearing what you have to say!
Post your own experiences, thoughts, and feedback to social media using the hashtag #healthy


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"The Outsiders" is a producer/dj-duo, based in Leiden, The Netherlands, that produces a large variety of sounds and subgenres within Drum & Bass music. The two young friends Jozef van der Veen (16) and Roeland van Rijnberk (17) have already received support from people like Noisia, NCT, Fre4knc, Monty, SKS, Dayle and more, with recent releases on Noisia's labels Division Recordings and Invisible Recordings, as well as SKS's label Vandal Records. The Outsiders met at school and they have been sharing track ideas with each other since 2013, often resulting in one of them trying to outdo the other. But after three years, the two decided to use each other's creativity, by making Drum & Bass music together as a duo, which is showing some great results so far. Their music varies from experimental, sound design heavy halftime, to deep, minimal rollers and hard hitting neurofunk.
Download presskit
Drum 'n Bass
Book The Outsiders for one of your events? Send an email to arjan (at) boembap.nl or use our contact form.


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Ron Morris
Morris: FCS playoffs should be prize for S.C. State
Worse ideas have come along in college football. It's just difficult to remember one.
The Mid-Eastern Athletic Conference is contemplating a requirement that its regular-season champion play against the champion from the Southwestern Athletic Conference for the historically black college national championship.
It would be the revival of the Heritage Bowl, which died a slow death in the late 1990s when fans realized the game held little or no significance.
Such a game makes sense for one reason only - money. With a TV deal and a healthy gate at a neutral site, the black national title game could be a financial boom to both leagues.
The problem is that by playing in the game, representatives from the MEAC and SWAC would forfeit any chance of playing in the FCS playoffs, which bring with it much national exposure for the participating team and its league. The SWAC already suffers from an inferiority complex and does not participate in the FCS playoffs.
"We've got to weigh whether we want to give up that national exposure in terms of FCS," said Charlene Johnson, South Carolina State's athletics director, "or whether we want to look at what dollars might be placed on the table."
Johnson said she would not take a side until all the facts are in. Her football coach, Buddy Pough, also wants to consider all options. But there is little doubting where he stands.
"I'm a playoff guy," Pough said.
Pough has been the S.C. State coach for eight seasons. His program is the envy of every other MEAC school. With a MEAC-record 19 consecutive league victories, the Bulldogs are the Alabama of black college football, and Pough is its Bear Bryant.
Pough's program has carried the MEAC flag for the past five seasons, earning a measure of respectability for the league that had been missing for decades.
Pough led the charge a couple of years ago for MEAC schools to begin playing nonconference games against FBS opponents. The league might take a beating on the field, Pough reasoned, but it was worth it to collect sizable paychecks while gaining national exposure.
For example, most fans in the Mountain West region never had heard of S.C. State until the Bulldogs played at Air Force in 2007. Not many fans knew of Delaware State until the Hornets played at Michigan this past season.
By winning back-to-back MEAC titles, Pough also has positioned S.C. State and the MEAC to finally win a game in the FCS playoffs. The Bulldogs lost at Appalachian State 37-21 in 2008, then nearly pulled off the upset this past season before again losing on the same opponent's home field, 20-13.
With the FCS playoff field expanding from 16 to 24 teams in 2010, S.C. State's chances of hosting a first-round game would seem to increase, as would their chances of winning the MEAC's first playoff game since Florida A&M and North Carolina A&T both did it in 1999.
So you can understand why Pough likes the playoffs.
"That's always the goal you can give to your team," Pough said of winning an national championship. "It's something that is pretty clearly defined. That's one of the goals we push to our team every year."
Still, Pough said he understands the arguments for staging a black national title game. There are programs in the nine-team MEAC that realistically never will compete at the same level as FCS playoff opponents.
Also, there are problems inherent with participating in the FCS playoffs. The visiting team seldom receives a large enough ticket allotment to accommodate its fan base. MEAC schools might be destined forever to travel in the first round, which means the playoffs are not a money generator.
"That's the reason sometimes there are frustrations," Pough said. "Sometimes, I might even say, 'I want to get out of (the playoffs).' "
Then Pough comes to his senses. He realizes there are two routes for the MEAC to earn respect nationally, and neither has to do with a black college national title game. First, a MEAC team must defeat an FBS opponent in the regular season. Second, a MEAC team must win an FCS playoff game.
When either or both of those happen, the MEAC will realize how silly it is to consider giving up the FCS playoffs for a black college national title game. Such a move would be short-sighted and for the benefit of the league only in the short term.
Of greater concern to the league and to S.C. State would be whether a move to a black national title game would force Pough to find another job. That would be the biggest loss of all to the MEAC and to S.C. State.


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It is so enriching to work with people who understand what it's like to be a creative. I've always wanted to photograph a intimate in home session and I knew Kyle and Michelle would be the couple to make that happen. I am thrilled that I had the opportunity to work along side my friend, Amaan Chowdhury who is amazing at film and Michelle who wrote a beautiful written piece for this blog. This is the final product of something I am extremely proud of and I am so ecstatic to share it with everyone.
Steep & Savor by Michelle Athena Norton
There's a tendency to overlook life's daily microcosms, or alternatively, and equally detrimental, to hone in on them too deliberately. The simple morning: a cup of tea unsavored by its indifferent drinker, brewed without much care. It might be because it has fallen into routine, has become rushed, or there's a distraction to be indulged. Whatever the justifications, it's hard not to lose sight of those small moments as a practice; a ritual, so to speak, where each act sets the tone for every motion that follows. This is all about us.
Kyle and I are the crafters of this morning brew: the leaves and beans are our potential, the cup is our home, and the time we steep; the flavor that is drawn out, our dynamic. We choose to savor it—these simple moments you see are but a pixel of the greater picture—this sole cup in a lifetime of burnt tongues, chipped porcelain, calm embraces, and thankful glances. There will always be overcooked pasta and spilt wine, awkward seductions and shrunken sweaters, but then there's that moment, the one where we realize, recover, and remember that everything is better together.
belleathena.com (Blog - Author)
othermag.co (Art & Literature Magazine - Founder/Editor-In-Chief)
@belleathena (Instagram Account)
Film by Amaan Chowdhury
Photography by Sufia Huq


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Skeebo Reichert has over 25 years as a professional photographer and has expanded services to include filmmaking. Clients include Greenland Enterprises, Carothers Executive Homes, Federal Industries, Texell Credit Union, and Temple Area Builders Association. He is a Temple HS graduate and returned to central Texas in 2006. He has a BFA in photography and sculpture and lives in Temple, TX, with his wife and two sons.
Next Steps…
Contact Skeebo to discuss your photo or film needs.


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Your community of Westover Hill Apartments is back with another blog post, and this time we're talking about the best coffee in town. Whether you're someone who swings by the coffee shop every morning on your way to work or someone who works at coffee shops all day long, finding that perfect cup of joe is no easy task.
Thankfully, there are dozens of options for coffee in San Antonio, and you don't always have to settle for the expensive chain store when you need your coffee fix. Give one of these local coffee shops a shot next time you need a pick me up!
We know this list is supposed to be all about the best coffee near your San Antonio luxury apartments, but the food at Barrio Barista is too good to not mention. You absolutely, positively have to try the Westside special—a dish that comes with a Barbacoa grilled cheese sandwich (!) and tomato soup. According to Yelp reviewers, this is one of the best dishes at any coffee shop in San Antonio.
The overall ambiance of Barrio Barista is worth mentioning too. Some Yelp reviewers talk about being "transported into a different world," as soon as they step inside this little coffee shop on the West Side. As for the drinks, we recommend you order the hot or cold Horchata latte.
This next cafe isn't a coffee shop, but we still included it on this list because of their caffeinated beverages. Tealicious is geared towards college students, but that just means it's a great place to get some work done. If you're unfamiliar with bubble tea, ask on of the staff members to explain it to you. We think you'll find that bubble tea is the ultimate refresher on a hot summer day. Tealicious also sells fruit smoothies that are totally customizable, so it's a great cafe to go to after a long workout.
A lot of people say that PRESS Coffee is the best coffee shop in San Antonio, and we have no reason to disagree with that assessment. If the weather's nice, you should definitely check out their backyard garden and terrace, which has plenty of seating on sunny days. The inside is filled with plenty of natural light, which creates the perfect environment in which to enjoy one of PRESS Coffee's phenomenal hazelnut lattes.
This cute little coffee house is inside a converted old house, so it seems like you're actually visiting an old friend when you step inside and order a coffee. Cozy is the best word to describe Sabinas Coffee House, so grab your laptop, find a nice comfy couch and prepare to stay awhile.
According to Yelp reviewers, Sabinas has an awesome little coffee station that allows customers to customize their drinks to the max. There's a whole lot more at this coffee station than just sugar packets and cream. Sabinas Coffee House also has plenty of food options on their menu, so bring your appetite along with your caffeine cravings.
As always, we appreciate you taking some time out of your busy summer schedule to take a look at the most recent edition of the Echelon at Monterrey Village blog. We hope we were able to help you find your new favorite coffee shop in West San Antonio. We'll be back soon another informative blog post for our residents, so don't forget to check this page again in a couple weeks! Also, be sure to follow us on social media to get the most up to date information from your community of apartments in Westover Hills.


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for current CTx Affiliate Honours Students
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text:
Back & Forth: Week of September 18th
We are so glad you have joined us for the Back & Forth blog. What an amazing week we had!
Looking Back
Monday - Wednesday
As we mentioned in our last post, we were in the midst of revival with Evangelist Olly Illarraza. We had a powerful time as he ministered on a variety of subjects, prayed for the sick and most of all gave prophetic words to virtually everyone in attendance. It turned out that what we had heard during the August Bible Conference in Chandler, AZ was true - if you don't have Olly, you don't really want revival.
We took a group of men to the streets of our city. We held up signs, passed out flyers to unsuspecting drivers at red lights, and preached the gospel. It's always a great time street preaching. If you have never tried it, prepare for an adrenaline rush like never before!
With completely in-house, homegrown talent, our Saturday Night Alive concert scene was fantastic. The live music, dramas and testimonies carried the anointing of the Holy Spirit. We had three visitors and an excellent time. We were even treated to a song by some of the kids from our Next Generation Ministry.
Pastor Dragoon was out of town preaching in Charleston, SC for Pastor Sean Duckett. That being the case the Sunday morning and evening services were left in the hands of the disciples, who stepped up to the plate. Led by Door Director Adam McFeaters, the disciples handled both services and the Sunday School with care. Adam preached in the morning service and In the evening we were treated to a Pastor Richard Ruby sermon from the August Chandler Conference entitled "Pearls."
We also wanted to take this time to remind you, in case you didn't already know, that all of our sermons are available as podcasts. The link to subscribe and download them can be found here, or by clicking on the content link below.
Looking Forward
We will be starting a new message series in our Mid-week ReCHARGE Services entitled, "Pray. Think. Vote.". Pastor Dragoon will be examining the most important issues that are facing this nation and the biblical worldview from which Christians need to be making their decisions this coming November.
We have a WEDDING coming up! This Saturday, September 24th, we welcome you to join Paul Wilcox and Adele Curiel as they are joined in holy matrimony. You may be thinking, "aren't weddings by invitation only?" The answer is yes, and if you are reading this, consider yourself invited!
We are also looking forward once again this coming weekend to World Evangelism Sunday! Make sure to find yourself in the house of God to be inspired to reach the nations with the Gospel.
We just want to thank you once again for being with us. We encourage you to join us this coming Sunday for our services at 11:00am and 6:30pm, and our Wednesday "Recharge" service at 7:30pm. We give God all the praise and glory for what He is doing in our city and our church.


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The basic data mining algorithms introduced may be enhanced in a number of ways.
- Evangeline Boyd
- 3 years ago
- Views:
1 DATA MINING TECHNOLOGIES AND IMPLEMENTATIONS The basic data mining algorithms introduced may be enhanced in a number of ways. Data mining algorithms have traditionally assumed data is memory resident, as for example in the case of the Apriori algorithm for association rule mining or basic clustering algorithms. Modifications to such algorithms are required for them to work efficiently with large persistent data sets. Also, much data is no longer held in persistent form in data warehouses. The data is generated at such a rate that it is infeasible to store it in that way. Instead, data is represented by transient data streams. This necessitates further modified solutions to the data mining techniques we have studied so far. 1
2 As scalable architectures based on commodity hardware such as Hadoop have emerged, techniques to support data mining on these architectures have been developed. Also, architectures which support analytics with both real-time processing of stream data and batch-oriented processing of historical data are required. Another problem is that once a data mining model has been developed, there has traditionally been no mechanism for that model to be reused programmatically by other applications on other data sets. Hence, standards for data mining model exchange have been developed. Also, data mining has traditionally been performed by dumping data from the data warehouse to an external file, which is then transformed and mined. This results in a series of files for each data mining application, with the resulting problems of data redundancy, inconsistency and data dependence, which database technology was designed to overcome. Hence, techniques and standards for tighter integration of database and data mining technology have been developed. 2
3 DATA MINING OF LARGE DATA SETS Algorithms for classification, clustering, and association rule mining are considered. CLASSIFYING LARGE DATA SETS: SUPPORT VECTOR MACHINES To reduce the computational cost of solving the SVM optimization problem with large training sets, chunking is used. This partitions the training set into chunks each of which fits into memory. The support vector parameters are computed iteratively for each chunk. However, multiple passes of the data are required to obtain an optimal solution. Another approach is to use squashing. In this, the SVM is trained over clusters derived from the original training set, with the clusters reflecting the distribution of the original training records. A further approach reformulates the optimization problem to allow solution by efficient iterative algorithms. 3
4 CLUSTERING LARGE DATA SETS: K-MEANS Unless there is sufficient main memory to hold the data being clustered, the data scan at each iteration of the K-means algorithm will be very costly. An approach for large databases would Perform at most one scan of the database. Work with limited memory. Approaches include the following: Identify three kinds of data objects: those which are discardable because membership of a cluster has been established; those which are compressible which while not discardable belong to a well-defined subcluster which can be characterized in a compact structure; those which are neither discardable nor compressible which must be retained in main memory. Alternatively, first group data objects into microclusters and then perform 4 k-means clustering on those microclusters.
5 An approach developed at Microsoft uses such approaches as follows: 1. Read a sample subset of data from the database. 2. Cluster that data with the existing model as usual to produce an updated model. 3. On the basis of the updated model, decide for each data item from the sample whether it needs to be retained in memory discarded with summary information being updated retained in a compressed form as summary information. 4. Repeat from 1 until termination condition met. 5
6 ASSOCIATION MINING OF LARGE DATA SETS: APRIORI With one database scan for each itemset size tested, the cost of scans would be prohibitive for the Apriori algorithm unless the database is resident in memory. Approaches to enhance the efficiency of Apriori include the following. While generating 1-itemsets for each transaction, generate 2-itemsets at the same time, hashing the 2-itemsets to a hash table structure. All buckets whose final count of itemsets is less than the minimum support threshold can be ignored subsequently since any itemset therein will itself not have the minimum required support. 6
7 Overlap the testing of k-itemsets and (k+1)-itemsets by counting (k+1)- itemsets in parallel with counting k-itemsets. Unlike in conventional Apriori in which candidate (k+1)-itemsets are only generated after the k-itemset database scan, in this approach a database scan is divided into blocks before any of which candidate (k+1)-itemsets can be generated during the k-itemset scan. Two database scans only are needed if a partitioning approach is adopted under which transactions are divided into n partitions each of which can be held in memory. In the first scan frequent itemsets for each partition are generated. These are combined to create a candidate frequent itemsets list for the database as a whole. In the second scan, the actual support for members of the candidate frequent itemsets list is checked. 7
8 Pick a random sample of transactions which will fit in memory and search for frequent itemsets in that sample. This may result in some global frequent itemsets being missed. The chance of this happening can be lessened by adopting a lower minimum support threshold for the sample, with the remaining database then being used to check actual support for the candidate itemsets. A second database scan may be needed to ensure no frequent itemsets have been missed. 8
9 An alternative approach to increase efficiency - FP- growth - uses a tree structure which holds frequent itemsets in a compressed form in a prefix-tree structure known as an FP-tree. Using this, only two database scans are needed to identify all frequent itemsets: The first scan identifies frequent items. The second scan builds the FP-tree in which each path from the root represents a frequent itemset. Consider again the set of transactions seen when the Apriori algorithm was introduced, but with two additional transactions T5 and T6: Trans_id T1 T2 T3 T4 T5 T6 List_of_items I1,I3,I4 I2,I3,I5 I1,I2,I3,I5 I2,I5 I3,I5 I1,I4,I5 Assume frequent itemsets with minimum support 50% are required. 9
10 The first database scan is the same as Apriori, generating 1 item itemsets and their support. This is then stored in a list of descending support count: I5 5 I3 4 I2 3 I1 3 I4 2 The second database scan builds the FP-tree by processing the items in each transaction in the order of the list generated in the first scan. A branch is created for each transaction, sharing paths from the root for previously constructed branches with the same items. Each node, representing an item, also contains a count which is incremented as each transaction including that node is added. Finally, a linked list is created from each item in the list generated in the first scan to the nodes representing that item in the tree. 10
11 Hence, after the second scan for transactions T1 T6 the following structure results: root:6 I3:1 I5 5 I3 4 I2 3 I1 3 I1:1 I5:5 I2:1 I1:1 I4 insufficient support I3:3 I2:2 I1:1 FP-growth then processes the FP-tree to identify frequent itemsets. 11
12 STREAM MINING Data streams arise in many application areas including real-time sensors, internet activity and scientific experiments. Such data is characterized by being: Infinite Arriving continuously Arriving at a high rate Arriving in a time series which is significant It is not possible for such data to be stored in a conventional database or data warehouse the data volumes and stream flow are too great. Hence, new techniques with new data structures and algorithms are needed. 12
13 These techniques include the following. Sampling: use a probabilistic method for choosing which data items within the stream should be processed. Load shedding: a sequence of data streams is not processed. Sketching: only a subset of the information within the stream is processed Synopsis data structures: summarization techniques are used to hold information about the stream in a more space efficient form. Aggregation: statistical measures are used to summarize the data stream. Approximation algorithms: given the computational complexity of exact mining algorithms, algorithms which give approximate solutions with defined error bounds are sought instead. Sliding window: analysis is restricted to most recent data within the stream. Algorithm output granularity: the development of algorithms which adapt to available resources such as processor load and memory availability. 13
14 These techniques have been used in the development of classical data mining tasks such as clustering, classification and frequent itemset identification within stream data. For example, in the case of frequent itemset identification, the FP-tree structure can be used to hold itemset information which is updated incrementally as transaction data arrives. As the first batch of transactions is received, the ordering of items can be determined on the basis of their support as in the FP-growth algorithm seen above and an FP-tree created. This ordering is not subsequently changed. As subsequent batches of transactions are received, the FP-tree can be updated to reflect the revised support for itemsets. Since it is infeasible to store itemset information for all batches indefinitely, a tilted window approach is often used: as new batches of transactions are received, the itemsets are computed for those new batches individually, while itemset information for older batches are then aggregated over longer time periods. 14
15 DATA MINING ARCHITECTURE TRENDS The Hadoop technologies already seen supporting data warehousing are increasingly being used to support data mining and analytics. For example, Pig has been used extensively in organisations including Twitter to support data mining and analytics. With the increasing importance of stream data, a particular architectural challenge is how to support the real-time processing required for stream data as well as the batch-oriented processing needed for historical data: the Hadoop technologies seen so far were originally designed with the latter in mind. One influential approach has been the lambda architecture which consists of 3 layers with all data dispatched to the batch and speed layers: A batch layer manages the append-only master data set and precomputes views on this A serving layer indexes these views to enable ad-hoc low latency queries A speed layer deals with recent data only to avoid the high latency of updates to the serving layer. 15
16 Hadoop technologies are well-suited to supporting the requirements of the batch layer. Column store or NoSQL technologies are often used to support the storage requirements of the serving layer. Stream technologies are required to support the speed layer, for example Storm: Storm is a distributed computing framework designed for real-time stream processing. The processing model is similar to MapReduce in that it supports a graphoriented workflow. However, while the MapReduce model is batch-oriented, Storm has been designed to support real-time processing of stream rather than batch data with streams continuing indefinitely. Storm was developed at BackType which was acquired by Twitter. It was developed and deployed for internal use before being made open-source. 16
17 DATA MINING STANDARDS Data mining standards and related standards for data grids, web services and the semantic web enable the easier deployment of data mining applications across platforms. Standards cover: The overall KDD process. Metadata interchange with data warehousing applications. The representation of data cleaning, data reduction and transformation processes. The representation of data mining models. APIs for performing data mining processes from other languages including SQL and Java. 17
18 CRISP-DM, PREDICTIVE MODEL MARKUP LANGUAGE PMML CRISP-DM (CRoss Industry Standard Process for Data Mining) specifies a process model covering the following 6 phases of the KDD process: Business Understanding Data Understanding Data Preparation Modeling Evaluation Deployment PMML is an XML-based standard developed by the Data Mining Group ( which is a consortium of data mining product vendors. PMML represents data mining models as well as operations for cleaning and transforming data prior to modeling. The aim is to enable an application to produce a data mining model in a form PMML XML - which another data mining application can read and apply. 18
19 Below is shown the PMML representation of an example association rules model for the following transaction data. 19
20 20
21 The association model XML schema specification follows. 21
22 22
23 The components of a PMML document consist of (the first two and last being used in the example model above): Data dictionary. Defines models input attributes with type and value range. Mining schema. Defines the attributes and roles specific to a particular model. Transformation dictionary. Defines the following mappings: normalization (continuous or discrete values to numbers), discretization (continuous to discrete values), value mapping (discrete to discrete values), aggregation (grouping values as in SQL). Model Statistics. Statistics about individual attributes. Models. Includes regression models, cluster models, association rules, neural networks, Bayesian models, sequence models. PMML is used within the standards CWM, SQL/MM Part 6 Data Mining, JDM, and MS Analysis Services (OLE DB for Data Mining) providing a degree of compatibility between them all. 23
24 COMMON WAREHOUSE METAMODEL CWM CWM supports the interchange of warehouse and business intelligence metadata between warehouse tools, warehouse platforms and warehouse metadata repositories in distributed heterogeneous environments. SQL/MM DATA MINING The SQL Multimedia and Applications Package Standard (SQL/MM) Part 6 specifies an SQL interface to data mining applications and services through SQL:1999 user-defined types as follows. User-defined types for four data mining functions: association rules, clustering, classification and regression. 24
25 Routines to manipulate these user-defined types to allow: Setting parameters for mining activities. Training of mining models, in which a particular mining technique is chosen, parameters for that technique are set, and the mining model is built with training data sets. Testing of mining models applicable only to regression and classification models, in which the trained model is evaluated by comparing with results for known data. Application of mining models in which the model is applied to new data to cluster, predict or classify as appropriate. This phases is not applicable to rule models in which rules are determined during the training phase. User-defined types for data structures common across these data mining models. Functions to capture metadata for data mining input. 25
26 For example, for the association rule model type DM_RuleModel the following methods are supported: DM_impRuleModel CHARACTER LARGE OBJECT (DM_MaxContentLength)) Import rule model expressed as PMML Return DM_RuleModel DM_expRuleModel() Export rule model as PMML DM_getNORules() Return number of rules DM_getRuleTask() Return data mining task value, data mining settings etc. 26
27 JAVA DATA MINING JDM Java Data Mining ( is a Java API developed under the Java Community Process supporting common data mining operations as well as the metadata supporting mining activities. JDM 1.0 supports the following mining functions: classification, regression, attribute importance (ranking), clustering and association rules. JDM 1.0 supports the following tasks: model building, testing, application and model import/export. JDM does not support tasks such as data transformation, visualization and mining unstructured data. JDM has been designed so that metadata maps closely to PMML to provide support for the generation of XML for mining models. Likewise, metadata maps closely to CWM to support generation of XML for mining tasks. The JDM API maps closely to SQL/MM Data Mining to support an implementation of JDM on top of SQL/MM. 27
28 OLE DB FOR DATA MINING & DMX SQL SERVER ANALYSIS SERVICES OLE DB for Data Mining, developed by Microsoft and incorporated in SQL Server Analysis Services, specifies a structure for holding information defining a mining model and a language for creating and working with these mining models. The approach has been to adopt an SQL-like framework for creating, training and using a mining model a mining model is treated as though it is a special kind of table. The DMX language, which is SQL-like, is used to create and work with models. 28
29 CREATE MINING MODEL [AGE PREDICTION] ( [CUSTOMER ID] LONG KEY, [GENDER] TEXT DISCRETE, [AGE] DOUBLE DISCRETIZED() PREDICT, [ITEM PURCHASES] TABLE ([ITEM NAME] TEXT KEY, [ITEM QUANTITY] DOUBLE NORMAL CONTINUOUS, [ITEM TYPE] TEXT RELATED TO [ITEM NAME] ) ) USING [MS DECISION TREE] The column to be predicted, AGE, is identified, together with the keyword DISCRETIZED() indicating that a discretization into ranges of values is to take place. ITEM QUANTITY is identified as having a normal distribution, which may be exploited by some mining algorithms. 29
30 ITEM TYPE is identified as being related to ITEM NAME. This reflects a 1- many constraint each item has one type. It can be seen from the column specification of the table inserted into, that a nested table representation is used with ITEM PURCHASES iself being a table nested within AGE PREDICTION. A conventional table representation would result in duplicate data in a single non-normalized table or data in multiple normalized tables. The USING clause specifies the algorithm that will be used to construct the model. Having created a model, it may be populated with a caseset of training data using an INSERT statement. Predictions are obtained by executing a prediction join to match the trained model with the caseset to be mined. This process can be thought of as matching each case in the data to be mined with every possible case in the trained model to find a predicted value for each case which matches a case in the model. 30
31 SQL Server Analysis Services supports data mining algorithms for use with: conventional relational tables OLAP cube data Mining techniques supported include: classification - decision trees clustering - k-means association rule mining Predictive Model Markup Language (PMML) is supported. SQL Server Analysis Services Data Mining Tutorials 31
32 DATA MINING PRODUCTS OPEN SOURCE A number of open-source packages and tools support data mining capabilities, including R, Weka, RapidMiner and Mahout. R is both a language for statistical computing and visualisation of results, and a wider environment consisting of packages and other tools for the development of statistical applications. Data mining functionality is supported through a number of packages, including classification with decision trees using the rpart package, clustering with k- means using the kmeans package, and association rule mining with Apriori using the arules package. Weka is a collection of data mining algorithms written in Java including those for classification, clustering and association rule mining as well as for visualisation. 32
33 RapidMiner consists of both tools for developing standalone data mining applications and an environment for use of RapidMiner functions from other programme languages. Weka and R algorithms may be integrated within RapidMiner. An XML-based interchange format is used to enable interchange of data between data mining algorithms. Mahout is an Apache project to develop data mining algorithms for the Hadoop platform. Core MapReduce algorithms for clustering, classification are provided, but the project also incorporates algorithms designed to run on single-node architectures and non-hadoop cluster architectures. 33
34 DATA MINING PRODUCTS ORACLE Oracle supports data mining algorithms for use with conventional relational tables. Mining techniques supported include: classification - decision trees, support vector machines... clustering - k-means... association rule mining Apriori Predictive Model Markup Language (PMML) support is included In addition to SQL and PL/SQL interfaces, until Oracle 11, a Java API was supported to allow applications to be developed which mine data. This was Oracle s implementation of JDM 1.0 introduced above. 34
35 From Oracle 12, the Java API is no longer supported. Instead, support for R has been introduced with the Oracle R Enterprise component. Oracle R Enterprise allows R to be used to perform analysis on Oracle database tables. A collection of packages supports mapping of R data types to Oracle database objects and the transparent rewriting of R expressions to SQL expressions on those corresponding objects. A related product is Oracle R Connector for Hadoop. This is an R package which provides an interface between a local R environment and file system and Hadoop enabling R functions to be executed on data in memory, on the local file system and HDFS. 35
36 READING P Bradley et al., Scaling Mining Algorithms to Large Databases, CACM, 45(8), J Gama, A Survey on Learning From Data Streams: Current and Future Trends, Progress in Artificial Intelligence, 1(1), 2012 (sections 3.1, 3.2 optional). J Lin and A Kolcz, Large-scale Machine Learning at Twitter, Proc. SIGMOD 12, May 2012 (sections 5, 6 optional). X Liu et al., Survey of Real-time Processing Systems for Big Data, Proc. IDEAS 14, July A Toshniwal et al., Proc. SIGMOD 14, June
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