Research

The Analytics Leader’s New Clothes

By Jack Phillips, Jul 17, 2015

No amount of spending, and no technology stack is going to make a company analytical. We’ve seen this fact lost on too many companies. Research shows that more than half of analytics projects fail, and technology is most frequently not the culprit.

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Inquiry Response: Machine Learning Best Practices

By IIA Faculty, Jul 08, 2015

Available to ERS Clients only

An IIA Research Client asks about best practices around decision making in a machine learning / big data environment.

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The State of Hadoop Adoption

By Jack Phillips, Jun 29, 2015

Available to ERS Clients only

In this phone briefing, Jack Phillips shares IIA’s new findings from the recent research report, “The Current State of Hadoop Adoption”. In this briefing, Jack explores the pros and cons of using Hadoop, including examples of how companies get value from Hadoop and the key challenges organizations face when implementing a Hadoop solution.

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You say you want Analytics, but…

By Cheryl Wiebe, Jun 16, 2015

I keep hearing manufacturers say they want to make data-driven decisions. They’ve read the news, they see the promise of the new sensor data, social sentiment, and behavioral data of their end consumers. But they are not doing it.

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Hadoop Adoption and Prediction

By IIA Faculty, Jun 15, 2015

Available to ERS Clients only

The IIA Faculty recently answered the question, “How would IIA characterize the state of Hadoop adoption? What does IIA anticipate to happen over the next 12-18 months?”

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What Angry Birds Can Teach Us About Analytics

By Bill Franks, Jun 11, 2015

As the complexity of your analytic ecosystem continues to grow, make sure that your organization is thinking ahead about how to simplify it for users. Personally, I like the Blockly concept and bet that your people will too.

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Governance in the New Analytic Zoo

By John Thuma, Jun 05, 2015

My point is regardless of the data shape, type, or where the data comes from governance is very critical, schema is critical, and transformation is also very critical. It’s essential to understand the importance of data consistency with respect to your data analytics journey.

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The Data Lake Debate

By IIA Faculty, Jun 05, 2015

Available to ERS Clients and Professional Members

Data Lakes offer businesses the ability to store vast amounts of raw data until it is ready for use. And if big data technologies like Hadoop can store any and all kinds of data for an insanely cheap cost, then why don’t we use it to capture, store, and process all our enterprise data? This question is at the heart of the Data Lake debate. While vendors and analysts continue to line up on both sides of this discussion, companies and agencies are still trying to figure out if they should even care.

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On May 27, IIA hosted Tamara Dull and Anne Buff of SAS Best Practices to debate the merits of Data Lakes. We fielded dozens of questions from our audience, and we’ve circled back to have Anne and Tamara respond to 13 of them.

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The 10 Levels of Analytics

May 26, 2015

Available to ERS Clients only

In this phone briefing John Elder and Andrew Fast describe the types of analytics inquiry and categories of modeling technology, illustrated with examples drawn from tabular data but also from advanced information types, such as sequences, text, and links.

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