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ODPi Members IBM, SAS and Index Analytics Share How to Leverage Business Intelligence and Big Data for better ROI in New White Paper

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ODPi, a nonprofit organization accelerating the open ecosystem of big data solutions, announced a new white paper that showcases how ODPi members IBM, SAS, Index Analytics and other technical contributors leverage Business Intelligence (BI) and Big Data for better ROI. The annual research takes the pulse of industry leaders and displays insight into how BI can be addressed by Hadoop through multi-structured data and advanced big data analytics.

“It doesn’t matter how much data you have; unless you can get the insight from it, it is just bits and bytes occupying the storage,” said Cupid Chan, CTO at Index Analytics. “As more traditional businesses evolve to digital transformation, they need to be leveraging true BI and Big Data into their products and services to get the results they want.”

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By 2020, the accumulated volume of big data will increase from 4.4 zettabytes to roughly 44 zettabytes or 44 trillion GB and companies will be charged with turning this data into insight. Big data technologies like Hadoop have become an ecosystem of open source projects that provide processing engines to perform data transformation and analysis. Many businesses, however,  don’t know how to combine the BI with Big Data to get insightful business value.

ODPi’s newest white paper presents best practices for combining BI and Big Data. ODPi members IBM and SAS and current technical contributors from other BI vendors including Qlik, MicroStrategy and Tableau share real end-user perspectives on how they are using big data tools, the challenges they face and where they are looking to enhance their investments.

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Their unique perspectives highlight includes:

  • The preferred BI/SQL Connector (Hive, Presto, Impala…etc) for their BI Tool to connect to Hadoop
  • Best practices to connect to both Hadoop and RDBMS
  • Recommended BI architecture to query data in Hadoop
  • How BI runs advanced analytics including Machine Learn algorithm on Hadoop

As an industry practitioner and ODPi lead for the BI & AI Special Interest Group (SIG), Chan discussed and surveyed a few project members and contributors in the technical community to benchmark findings in this annual survey.

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“As data sizes continue to grow, it becomes harder and harder to gain visual and analytic insights from it,” said Craig Rubendall, Vice President, Platform Research and Development at SAS. “To be successful, it is imperative to use practices and products built to handle the demands of this environment. SAS is proud to collaborate with the other contributors to share our experience and knowledge.”

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