Research

Hadoop and the Enterprise Data Warehouse, Simplified

By IIA Faculty, Nov 16, 2014

Available to ERS Clients only

When Apache Hadoop, the open source poster child for big data technologies, hit the streets eight years ago, it rattled the cages of traditional BI and data warehousing professionals. There was a lot of speculation about whether Hadoop would replace existing infrastructures, or complement them, or just be another hyped-up technology fad. We now know that Hadoop is not a fad nor is it here to replace existing infrastructures. The discussion on the table now is how to best utilize Hadoop - even if you don’t have big data.

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Intel’s View of the Role of Technology and Data to Transform Healthcare

By Chris Gough, Ketan Paranjape, Nov 07, 2014

Available to ERS Clients only

Intel’s commitment to the healthcare market can be traced around the globe from devices and ruggedized computing platforms to mobile diagnostics and telemedicine to new cloud computing efforts. Each of these examples aligns with Intel’s healthcare vision to “bring computing technologies and solutions to improve healthcare cost, quality and access to billions of people in the world.” As outlined by Eric Dishman, General Manager of Intel Health & Life Sciences, there are four global megatrends that Intel is addressing: Global Aging, Caring in Teams, Paying for Value and Personalizing the Next Generation.

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Making Meaningful Predictions in the Fast Lane

By Mark Dobeck, Jerry Baulier, Scott McCormick, Oct 10, 2014

Available to ERS Clients only

Event stream processing uses wireless and wireline transmissions of streaming events/transactions at rates of up to millions of events per second from multiple sources; the transmissions are real-time and low latency to the microsecond level. The use of and interest in event stream processing continue to evolve in virtually every industry and market.

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Five Clusters of Opportunity with Big Data

By Robert Morison, Sep 23, 2014

In what areas of your business can big data have the greatest impact? In many organizations, that’s a very difficult question to answer. Why? Big data offers so many new opportunities and so many different kinds of opportunities, from using real-time sensor data to mining the unstructured conversation on social media.

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Do Your Metrics Matter?

By Kimberly Nevala, Sep 16, 2014

Your organization has well-defined metrics. Executives track them diligently. Managers include them in status reports. Key Performance Indicators (KPI) are prominently featured in annual reports and PR. So isn’t the company, by definition, data-driven?

The answer, unfortunately, is: not necessarily.

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Inquiry Response: The ROI of Data Governance

By IIA Faculty, Sep 11, 2014

Available to ERS Clients only

We are in the process of proposing an organizational structure (more formal than we’ve had thus far) for data governance. One of the requests from our exec team was to provide more detail regarding Return on Investment (financial and other) for a DG program. Does IIA have any resources, methods, for building a justification and ROI for DG? Or how would you suggest I tap into IIA resources for this?

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Prepare to be Amazed by Immersive Intelligence

By Bill Franks, Sep 11, 2014

The range of immersive visual worlds that can be created is limited only by the types of data that exist and how that data can be utilized. In other words, it is virtually limitless.

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Health Analytics in a Person Centered World Part II: The Person-Centered Health Analytics Toolkit

By Dwight N. McNeill, Sep 05, 2014

Available to ERS Clients only

Person Centered Health Analytics (pchA) sets a new course for analytics. Health outcomes are no longer confined to the two P’s (providers and payers). Outcomes are centered squarely on the forgotten P, people. It is not about business intelligence for improving revenues and reducing costs; it’s focused squarely on helping people to live a long and healthy life. It is not about worshiping the possibilities of information technology; it’s about getting information technologies to engage people as drivers of their own health.

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Text Mining Versus Text Analytics

Aug 29, 2014

Available to ERS Clients only

We define textual analysis to be the automated analysis of unstructured textual data, containing within it the methodologies of text mining and text analytics. Leading textual analysis use cases include Sentiment Analysis, Natural Language Processing (NLP), Information Extraction, and Document Categorization. Historically, text analytics practitioners have backgrounds in computational linguistics and knowledge management, whereas text mining practitioners come from the fields of data mining and statistics.

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Evaluating Hadoop for Enterprise Big Data ETL

By Ajay Chandramouly, Aug 26, 2014

Like many leading IT organizations, my employer, Intel, has embraced the challenge of extracting business value from big data and turning the insights gained into a competitive advantage. Part of this challenge involves the process used to extract big data from multiple sources, then cleanse, format, and load it into a data warehouse for analysis, a process known as ETL (extract, transform, and load). But the conventional wisdom around ETL is shifting.

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