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This article is part of the Issue 1 January 2012 issue of Big Data: Separating the hype from the reality
Big data is everywhere these days. Marketing materials are bursting with references to how products have been enhanced to handle big data. Consultants and analysts are busy writing new articles and creating elegant presentations. But the sad reality is that big data remains one of the most ill-defined terms we’ve seen in many a year. The problem is that data volume is a metric that tells us little about the data characteristics that allow us to understand its sources, its uses in business and the ways we need to handle it in practice. Even the emerging approach of talking about big data in terms of volume, velocity and variety leaves a lot to be desired in terms of clarity about what big data really is. Business Drivers and Origins So, what is the problem? And, more to the point, is there an answer? The problem is that big data in a technical sense, beyond the common characteristic of “bigness,” has little else in common. Hence the difficulty in coming up with a single, all-encompassing definition. However, in a business sense, there is one common ... Access >>>
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The hype vs. the reality of big data
by Barry Devlin
The air is thin at the top of the hype curve, so breathe deeply as we explore the reality of big data—and the changes it entails for BI and data warehousing systems.
- The hype vs. the reality of big data by Barry Devlin
Applying agile methods to data warehouse projects
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Agile development processes can take a lot of the pain out of building data warehouses and enable project teams to deliver functionality, and business value, on a rolling basis.
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