{"id":1251,"date":"2016-01-05T14:22:54","date_gmt":"2016-01-05T19:22:54","guid":{"rendered":"https:\/\/solutionsreview.com\/data-integration\/?p=1251"},"modified":"2016-10-05T09:44:57","modified_gmt":"2016-10-05T13:44:57","slug":"big-data-as-a-service-the-time-is-now","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/data-integration\/big-data-as-a-service-the-time-is-now\/","title":{"rendered":"Big Data as a Service: The Time is Now"},"content":{"rendered":"

\"Big<\/p>\n

By Gary Oliver, CEO at Blazent<\/strong><\/p>\n

BDaaS comes of age in 2016, bolstering innovation<\/em><\/p>\n

Did you know that roughly one-third of all chief data scientists spend up to 90 percent of their time \u201ccleaning\u201d raw data? That\u2019s an astounding number. Rather than focusing on the design and implementation of complex processes across large-scale datasets, bad data has relegated many data scientists to the job of data janitors who must sift through mountains of erroneous information. This type of inefficiency costs enterprises millions of dollars in lost productivity, revenue and opportunity. In fact,\u00a0Gartner estimates<\/a> that poor data quality costs the average business $13.5 million each year.<\/p>\n

Thankfully, all is not lost. Big Data as a Service (BDaaS) has the potential to free data scientists from the shackles of bad data, and elevate them back into positions of innovation and authority. By delivering essential, on-demand solutions that bridge the gap between data scientists and the enterprise, BDaaS can help companies overcome the challenges of poor data quality and deliver actionable Business Intelligence<\/a>. For these reasons, Big Data as a Service will take center stage in 2016.<\/p>\n

The Power of BDaaS<\/strong><\/p>\n

To harness the power of Big Data, enterprises need complete, error-free datasets on which to perform intelligent analytics<\/a>. Tackling Big Data typically requires substantial upfront costs on components and infrastructure. On top of initial setup costs, storing and managing large quantities of data require significant, ongoing expenditures.<\/p>\n

In lieu of taking on the operational and financial risk of creating in-house Big Data infrastructures, enterprises will increasingly leverage BDaaS solutions to quickly and cost effectively execute Big Data initiatives. BDaaS\u2019 sweet spot is its ability to provide enterprise users with widespread accessibility to Big Data interfaces and tools within a self-managed, auto-scaling infrastructure. This adaptable, on-demand environment is what allows companies to achieve a level of enterprise-class access to all its data on a very small operational footprint. In doing so, enterprises can realize the agility, fluidity and flexibility needed to capitalize on Big Data opportunities.<\/p>\n

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BDaaS and Data Intelligence<\/strong><\/p>\n

While Big Data as a Service describes a wide variety of functions that are outsourced to the cloud \u2013 ranging from data collection to the delivery of analytical tools that examine the data to perform intelligent analysis \u2013 it\u2019s in the data intelligence space that BDaaS shines.<\/p>\n


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With BDaaS data intelligence, companies can:<\/p>\n