Building flexible apps from big data sources



Building flexible apps from big data sources.

SQL to Hadoop and back again, Part 1: Basic data interchange techniques

I’ve got a new article, which is part of a new three-part series, on moving data between SQL and Hadoop, both the export to Hadoop and importing processed content back into an SQL store.

In this first one, we look at the basic mechanics and considerations before you start the migration of data, such as the data format, content, and export techniques.

Read: SQL to Hadoop and back again, Part 1: Basic data interchange techniques

Data Mining in a Document World

As databases evolve, learning how to get the best out of the different solutions out there is the key to understanding and extracting the data in the way you need from your required data store. Document databases, like MongoDB, CouchDB, Couchbase Server and many others provide a completely different model and set of problems for interfacing and extracting data.

You need to be able to understand your structure, how you can query the information, and how to perform different data mining techniques on what is very obviously a completely different structure of information.

In this article, I try to take you through the basics of data mining when using a document database.

Read: Data mining in a document world

Data Mining Techniques

I have a new article on the basics of data mining techniques so that you can better understand some of the key principles behind the different methods and principles of data mining. 

From the abstract:


Read: Data Mining Techniques

Document Databases in Predictive Modeling



Read Document databases in predictive modeling