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How Will MapReduce Technology, Such as Hadoop, Drive BI in the Next Few Years

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David Linthicum: How will MapReduce technology, such as Hadoop, drive BI in the next few years?

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  • As I wrote here http://www.ebizq.net/blogs/2009/12/top_10_bi_predictions_for_2010.php , my beliefs regarding Hadoop and related data management frameworks are as follows:

    The undeniable arrival of the era of big data will lead to further proliferation in data management alternatives. While analytic-centric OLAP databases have been around for decades such as Oracle Express, Hyperion Essbase, and Microsoft Analysis Services, they have never held the same dominant market share from an applications consumption perspective that the RDBMS vendors have enjoyed over the last few decades. No matter what the application type, the RDBMS seemed to be the answer. However, we have witnessed an explosion of exciting data management offerings in the last few years that have reinvigorated the information management sector of the industry. The largest web players such as Google (BigTable),Yahoo (Hadoop), Amazon (Dynamo), Facebook (Cassandra) have built their own solutions to handle their own incredible data volumes, with the open source Hadoop ecosystem and commercial offerings like CloudEra leading the charge in broad awareness. Additionally, a whole new industry of DBMSs dedicated to Analytic workloads have sprung up, with flagship vendors like Netezza, Greenplum, Vertica, Aster Data, and the like with significant innovations in in-memory processing, exploiting parallelism, columnar storage options, and more. We already starting to see hybrid approaches between the Hadoop players and the ADBMS players, and even the largest vendors like Oracle with their Exadata offering are excited enough to make significant investments in this space. Additionally, significant opportunities to push application processing into the databases themselves are manifesting themselves. There has never been the plethora of choices available as new entrants to the market seem to crop up weekly. Visionary applications of this technology in areas like metereological forecasting and genomic sequencing with massive data volumes will become possible at hitherto unimaginable price points.

  • I think advances in BI platform power benefits user adoption very directly. Latency, even a few seconds, turns off the average business user. Even when data warehouses were "smaller" many BI users have had to live with this issue.

    With data stores tending to grow over time with the preservation of all historical data, this dissatisfier continues a perennial problem with wide BI tool adoption despite hardware processing improvements. So advances in data access, especially in internal enterprise applications, is going to be major positive in driving further BI ubiquity.

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