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8 Big Data Trends for 2016

By   /  December 7, 2015  /  No Comments

trenby Angela Guess

Ben Rossi recently opined in Information Age, “The trend of more people doing more with their data at speed will continue as 2016 will be the year that best practice becomes clear. The spread of self-service data analytics, along with widespread adoption of the cloud and Hadoop, are leading to many changes that are creating change and excitement in the industry, which businesses will either take advantage of or ignore at their peril. Here are eight predictions on the shape of data in the New Year.”

First up, according to Rossi, “(1) The NoSQL takeover. NoSQL technologies, commonly associated with unstructured data, have seen significant adoption over the last 12 months. Going forward, the shift to NoSQL databases as a leading piece of the enterprise IT landscape becomes clear as the benefits of schema-less database concepts become more pronounced. Nothing shows the picture more starkly than looking at Gartner’s Magic Quadrant for Operational Database Management Systems, which in the past was dominated by Oracle, IBM, Microsoft and SAP. In contrast, in the most recent Magic Quadrant, the NoSQL companies, including MongoDB, DataStax, Redis Labs and MarkLogic, are set to outnumber the traditional database vendors in Gartner’s Leaders quadrant of the report.”

His list continues, “(2) Apache Spark lights up big data. Apache Spark has moved from a being a component of the Hadoop ecosystem to the big data platform of choice for a number of enterprises. Spark provides dramatically increased data processing speed compared to Hadoop and is now the largest big data open-source project, according to Spark originator and Databricks co-founder, Matei Zaharia. More and more compelling enterprise use cases around Spark are emerging, such as at Goldman Sachs, where Spark has become the ‘lingua franca’ of big data analytics.”

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photo credit: Flickr/ See-ming Lee

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