{"id":448,"date":"2013-12-18T10:29:06","date_gmt":"2013-12-18T15:29:06","guid":{"rendered":"https:\/\/solutionsreview.com\/data-integration\/?p=448"},"modified":"2013-12-18T10:48:55","modified_gmt":"2013-12-18T15:48:55","slug":"2014-big-data-analysis-priorities-from-data-integration-leader-pentaho","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/data-integration\/2014-big-data-analysis-priorities-from-data-integration-leader-pentaho\/","title":{"rendered":"2014 Big Data Analysis Priorities from Data Integration Leader Pentaho"},"content":{"rendered":"

\"Pentaho<\/a>Back in October Pentaho developed four main priorities for big data analysis based on end-user research by Enterprise Management Associates (EMA) and 9sight Consulting and with 2014 fast approaching we thought we might share some of their findings. \u00a0Pentaho reveals that main priorities for enterprises that have addresses big data initiatives and analysis will revolve around blending data, predictive analytics and real-time query optimization.<\/p>\n

Some of the main findings from the EMA and 9sight Consulting research that lead to Pentaho\u2019s 2014 predictions include big data implementations in production rose from 27% in 2012 to 34.3% this year. 68% of companies are running two or more big data projects as part of their big data initiatives. Big data business drivers include speeding time for operational or analytical workloads, increasing competitive advantage with flexibility of data used and the need to combine sales information into operational analytics.<\/p>\n

The follow are a few excerpts from Pentaho\u2019s October press release that highlight the priorities they set forth:<\/p>\n

\u201cData blending for hybrid data architectures<\/strong>\u00a0<\/b>\u2013 as companies move into production, businesses need to access different types of data sources held in different systems and blend them without losing data integrity including big data sources.\u201d<\/p>\n

\u201cReal-time analytics on Hadoop<\/strong>\u00a0<\/b>\u2013 the \u2018need for speed\u2019 revealed in the EMA\/9sight research is confirmed by Pentaho customers demanding support for Storm, a real-time ETL technology.\u201d<\/p>\n

\u201cPredictive analytics<\/strong>\u00a0<\/b>\u2013 Taking advantage of batch processing in Hadoop can help businesses make more accurate predictions leveraging big data for fraud detection, upselling and a range of predictive applications.\u201d<\/p>\n

\u201cFree Form Search<\/strong>\u00a0<\/b>(SolR, Cloudera Search, Apache Search)\u00a0<\/b>\u2013 Companies seeking new discoveries from corporate and big data sources can use fast and flexible search technologies.\u201d<\/p>\n

Click here to read the full release<\/a> and for much more on these 2014 priorities for big data analysis from Pentaho.<\/p>\n","protected":false},"excerpt":{"rendered":"

Back in October Pentaho developed four main priorities for big data analysis based on end-user research by Enterprise Management Associates (EMA) and 9sight Consulting and with 2014 fast approaching we thought we might share some of their findings. \u00a0Pentaho reveals that main priorities for enterprises that have addresses big data initiatives and analysis will revolve […]<\/p>\n","protected":false},"author":2,"featured_media":460,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1,3],"tags":[],"acf":[],"yoast_head":"\n2014 Big Data Analysis Priorities from Data Integration Leader Pentaho<\/title>\n<meta name=\"description\" content=\"Pentaho says that main priorities for enterprises that have addresses big data initiatives will revolve around blending data, predictive analytics and more\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, 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