{"id":3225,"date":"2012-09-11T07:00:25","date_gmt":"2012-09-11T15:00:25","guid":{"rendered":"http:\/\/www.formtek.com\/blog\/?p=3225"},"modified":"2012-09-11T07:00:25","modified_gmt":"2012-09-11T15:00:25","slug":"big-data-relational-databases-still-dominate-big-data-projects","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/big-data-relational-databases-still-dominate-big-data-projects\/","title":{"rendered":"Big Data: Relational Databases Still Dominate Big Data Projects"},"content":{"rendered":"<div id=\"_mcePaste\">62 percent of companies say that they&#8217;ve deployed Big Data applications. \u00a0But the applications they&#8217;re using for Big Data sound a lot like traditional software applications. \u00a0That&#8217;s the result of a survey taken and reported by <a title=\"Report by JasperSoft on Big Data\" href=\"http:\/\/www.jaspersoft.com\/press\/jaspersoft-big-data-survey-highlights-global-adoption-trends-and-use-cases\" target=\"_blank\">JasperSoft<\/a>.<\/div>\n<div>&nbsp;<\/div>\n<div>60 percent say that rather than using Big Data tools like Hadoop or MongoDB, they prefer to use standard relational databases for analyzing their Big Data. \u00a0And nearly 80 percent say that the source for their Big Data is enterprise software applications. \u00a033 percent are tapping into their Customer Relationship data; 31 percent are using their Financial or ERP systems, and 28 percent are getting data from their eCommerce systems. \u00a0Machine-generated content, like web logs are used in 68 percent of Big Data projects, compared to 46 percent of projects using human-generated data like social media and blogs.<\/div>\n<div>&nbsp;<\/div>\n<div>The <a title=\"Jaspersoft Report on Big Data Analytics\" href=\"http:\/\/www.zoomerang.com\/Shared\/SharedResultsSurveyResultsPage.aspx?ID=L2B66ZBVLZLZ\" target=\"_blank\">Jaspersoft report<\/a> found that the \u00a0top five Big Data use case categories were:<\/div>\n<div>&nbsp;<\/div>\n<div>\n<ul>\n<li><strong>48 percent <\/strong>&#8211; Customer experience analytics<\/li>\n<li><strong>37 percent<\/strong> &#8211; Customer analytics<\/li>\n<li><strong>28 percent<\/strong> &#8211; Marketing campaign optimization<\/li>\n<li><strong>27 percent<\/strong> &#8211; Financial risk analysis<\/li>\n<li><strong>27 percent<\/strong> &#8211; Marketing competitive analysis<\/li>\n<\/ul>\n<\/div>\n<p>The most common types of output from Big Data analytics were reports (76 percent), data visualization (64 percent), data integration (59 percent), predictive analytics (54 percent), and search (50 percent).<\/p>\n<p>It seems clear that momentum is building for Big Data applications, but this survey suggests that many are equating Big Data with Business Intelligence and Data Analytics.<\/p>\n<div class=\"lightsocial_container\"><div class=\"lightsocial_element\"><a class=\"lightsocial_a\" 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