6/7/2017 12:01:36 PM
AtScale unveils their new 5.5 platform update
Big Data Risk Mitigation,Big Data Platform,Big Data Analytics
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App Developer Magazine

AtScale unveils their new 5.5 platform update



Richard Harris Richard Harris in Big Data Wednesday, June 7, 2017
3,133

Big data anayltics and risk management to come iwth AtScale's new 5.5 update.

The adoption of the data lake over the past few years has proven that enterprises want a way to store vast amounts of raw data in its native format until needed for consumption. New database platforms like Hadoop or Google BigQuery have provided affordable solutions to let enterprises store data. However, when this data is not put to use, Data Lakes became Data Swamps. That's what AtScale looks to change with the latest unveiling of their latest 5.5 update.

“Historically, data stored in data lakes goes unused because the organization has not figured out a way to match the performance, security or business tool integration they created with their legacy system,” says Matt Baird, CTO and co-founder at AtScale. “When they deploy AtScale, customers not only get better performance than traditional systems, they can do it on unlimited data and seamless end-user experience.”

From “Lock-In” to “Lift and Shift”


Beyond the need to make their data lakes perform like traditional MPP databases with limitless data, enterprises are looking to mitigate their Big Data risks across on-premises or cloud deployments. Enterprises that have heavily invested in one particular data platform delivery mode are wary of what’s called “lock-in” (an excessive investment with one vendor or one type of technology, which can reduce an enterprise’s agility and competitive advantage).

Consider the experience of a large retailer based in the US. Its thousands of store managers live by their daily inventory reports. These reports, run on Microsoft Excel, contain sophisticated calculations that span across a long historical period but, which must be refreshed in seconds to allow managers to make timely decisions. This organization's IT department spent hundreds of millions of dollars in traditional data warehouse software and hardware to guarantee performance. Until it realized the potential of Hadoop and the Cloud. In less than six months, this retailer migrated its data from a traditional MPP to Hadoop, and then to the Cloud, saving millions of dollars. This enterprise future-proofed its data investment with a smart “lift and shift”, performed without store managers missing a beat.

“AtScale was early to spot the opportunity to bring high performance interactive analytics to big data platforms,” says Matt Aslett, Research Director, Data Platforms and Analytics, 451 Research. “The company’s expanded vision, driven by the best practices learnt from customer successes, broadens its applicability and addressable audience.”

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