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Showing posts with the label big data platforms

Oracle’s Giant Leap for Democratization of Big Data

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Gartner’s magic quadrant analysis for Business Intelligence and Analytics platforms have mainly three criteria to assess platforms which I think are spot-on. They focus on enable (data with minimal technical know-how), produce (efficiency of data analytics and reports building) and consume (from various platforms, etc.). The theme is clear as businesses do not have the patience to wait for large implementation projects or development cycles. They want to know key drivers, critical insights, hidden opportunities and decision-making data points on various devices right away. Learn more about Oracle Cloud Services . With the emergence and popularity of Big Data platforms, businesses are able to gain insights from data that was useless and too large to process in past. Platforms like Hadoop and Spark enable organizations to process structured and unstructured data at amazing speed and scale to gain quick insights. But major drawback of Big Data platforms is that organizations need t...

Data Quality Powered by Big Data

Enough has been said about the importance of data in an enterprise. Data has the power to drive decisions, deliver actions, bring efficiency and directly impact the bottom line. To realize the true potential of data, organizations need to make sure that their data is accurate, complete, concise, easily accessible, secured and consumption ready. In a highly competitive environment today, companies don’t have the luxury of vetting through many spreadsheets and documents. Data-driven decisions must be timely to be effective. Almost every organization has many sources of data inputs containing same or different data attributes for the same entities. For example, information about  customer  entity can flow-in through web & mobile self-service, social media outlets, census and other government data sources, credit agencies, log files etc. A lot of times information received for a unique customer is conflicting and a lot of times information about two different customers ...