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Replacing Big Data And Emergence of Multi-Cloud Era

Big Data is coming to an end, the era where we saw the major organizations focusing on a collection of data will now be shifting to processing of data that can happen in real-time. Big data is now a business asset that is supporting the next generation of multi-cloud support, real-time analytics, and machine learning.   The official end for many big data engineers happened when Tom Reilly announced resignation from Cloudera on June 5, 2019, and then we had the subsequent market capitalization drop. It was even supported by the recent announcement of shutting down MapR late in June 2019, that is supporting the actually end for Big data that has come to an end.

Big data started with the initial role of data capture that gained momentum across various social media channels supporting, that fundamentally changed the way enterprises seek to work with multiple orders of magnitude increase in the data volume. Then came the added process of analytics that could bring the enterprises with improving the data quality and data governance for the business. It keeps the focus on the ongoing valuation of data as an enterprise asset. The initial generation of Hadoop based Big Data has reached a maturity phase, where the role in enterprise data is established. Big data is no longer a breathless hype of cycle of infinite growth, but now it’s a well-matured technology.

The shift is a fundamental understanding of perceiving a data is making the enterprise data go beyond traditional enterprise database assumptions, led to the transformative data use cases as the companies realized that data could be providing business insight, developing the growth fraction that initial lacked. Although the Big data/ Hadoop was valuable support when it came to supporting machine learning tasks using the batch processing, they, however, lacked more traditional analytics need that many businesses required daily. Tools such as Hive, Dremel, and spark were used on top of Hadoop to support analytics, but it never came fast enough to replace the data warehouse.

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