{"id":1278,"date":"2014-08-21T09:07:35","date_gmt":"2014-08-21T09:07:35","guid":{"rendered":"https:\/\/www.happiestminds.com\/blogs\/?p=1278"},"modified":"2026-03-06T06:31:51","modified_gmt":"2026-03-06T06:31:51","slug":"managing-enterprise-big-data-building-the-right-platform","status":"publish","type":"post","link":"https:\/\/www.happiestminds.com\/blogs\/managing-enterprise-big-data-building-the-right-platform\/","title":{"rendered":"Managing Enterprise Big Data \u2013 Building the Right Platform"},"content":{"rendered":"
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Although the popularity of Big Data<\/a> is increasing day-by-day, the concept stems from a very simple theory. Businesses mostly rely on transactional data, stored in relational databases, for decision making. However, there\u2019s also a treasure-trove of unstructured, non-transactional data available to them in the form of emails, blogs, photographs, sensors, etc. that can be harnessed for gaining useful insights. Today, since storing and computing data has become more affordable, organisations can utilize this non-traditional yet potentially valuable information for analysis and business intelligence. And this is precisely what Big Data helps companies do \u2013 manage volume, velocity and variety of data.<\/p>\n

Since Big Data helps businesses organise and analyse diverse data types and capitalise on hidden relationships, it is imperative for them to manage their enterprise big data properly. But not only is moving and transforming it difficult, integrating it with organisational data flows, while also maintaining quality, is also a daunting task. So organisations need to build an efficient Big Data platform<\/a> based on their needs, the infrastructural requirements for which span:<\/p>\n