Integrating Analytic Data Using Data Virtualization

More Data = Better Analysis

The analytic data domain includes all kinds of data, including:

  • traditional enterprise data from sources like the Enterprise Data Warehouse;
  • big data from sources like Hadoop;
  • cloud data from SaaS applications and public providers;
  • social media data from sites like Facebook and Twitter; and
  • personal/desktop data from spreadsheets and flat files.

Data virtualization is an optimal solution to integrate all these sources, thereby improving analysis and business insight.

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Data Challenges in the Analytics Pipeline

Data is the lifeblood of analytics — the more diverse the better.

In their best-selling book, Big Data: A Revolution That Will Transform How We Live, Work, and Think, Mayer-Schonberger and Cukier describe the synergy that occurs when previously unrelated and disparate data is brought together to uncover hidden insights. But these advanced analytics data requirements are a double-edged sword as these more diverse sources complicate data integration and constrain progress.

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Solving the Analyst’s Data Problem

Recently I have been talking to a number of data scientists and business analysts about what they actually do when performing a new analysis of some nature. Their processes were quite surprising because they were far more data intensive and far less modeling / analysis intensive than I had thought.

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Can Data Virtualization Address the Data Integration Bottleneck?

We all understand the business value of BI and analytics as enablers for growth, a means to attract and retain customers, or a way to drive innovation and reduce costs.

CIOs do as well. Both Gartner’s Amplifying the Enterprise: The 2012 CIO Agenda and IBM’s Global CIO Study 2011 place BI and analytics atop CIO’s technology priorities.

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The Greatest Data Virtualization Day Ever!

Each year, I am responsible for leading the premier event in data virtualization, Data Virtualization Day.  It’s a huge responsibility and even bigger endeavor.  But the rewards are amazing, especially when the event is as successful as Data Virtualization Day 2012.

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Analytics the Driver for Latest Data Virtualization Platform Release

This week Composite Software introduced the version 6.2 of the Composite Data Virtualization Platform.

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TDWI’s Data Virtualization Class A Big Hit

I left for vacation right after attending Dave Wells’ Data Virtualization Class at TWDI in San Diego on August 1st, so I hadn’t had the chance to comment on the new course. It’s been a couple of weeks, but I still have positive vibes from the class, as did many of the attendees.

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TDWI Goes for Data Virtualization

You know times are changing if you see The Data Warehouse Institute (TDWI) offer a class that involves anything ‘virtual.’ But the data warehouse has been evolving, and today and tomorrow’s DW is not your father’s DW anymore. 

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Data Virtualization Is Hot at the Gartner BI Summit

A Fantastic, Immersive Opportunity

Last week I attended the Gartner BI Summit in Los Angeles.  While I am an avid follower of Gartner’s Information Management, Analytics and BI research, it was great to hear this content directly from the analysts and gauge the reaction of the thousand plus attendees.

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A Look Under the Data Virtualization Hood – Part 2

Three Key Environments Make Up the Platform

Data virtualization middleware platforms provide the functionality described above within integrated offerings that support the full software development life cycle, high-performance run-time execution and reliable, 24x7x365 operation.

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