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Data automation and scheduling becoming mission critical to big data

Over the years companies have explored many avenues to handling and manipulating large amounts of data. However, with the advent and growth of the cloud and big data, the resulting explosion in the quantity of data being analyzed and the seemingly endless number of data sources, the need for fast, flexible and smart automation of the data workflow that can adapt and handle changes is now more important than ever.

“It’s no longer about taking one or two use cases around big data and driving success. Data and intelligence is now at the center of everything a company does,” said Basil Faruqui, solutions marketing manager at BMC Software Inc.

Faruqui spoke with John Furrier (@furrier) and George Gilbert (@ggilbert), co-hosts of theCUBESiliconANGLE Media’s mobile live streaming studio, during the BigData SV 2017 conference in San Jose, CA. (*Disclosure below.)

The discussion centered on how data flow and management is adapting as the big data environment continues to rapidly expand, as well as how data automation is becoming mission-critical for many companies relying on real-time data intelligence.

Automation is the heart of big data management

The most important factors to having success in the big data environment are not new. Batch automation and job scheduling are at the heart of modern big data management, now as well as in the past, according to Faruqui. Finding ways to automate as much of the workflow as possible is critical to adaptable, effective, intelligent and accurate data management.

“Scheduling and workflow automation is absolutely critical to the successes of big data projects,” said Faruqui. “And this is not something new. Hadoop is only 10 years old, but other technologies that have come before Hadoop have relied on this foundation for driving success.”

The number of situations facing chief information officers and data modelers are complex and limitless. Everything, from designing customer engagement models to building new development ecosystems to back office optimization requires not only a firm grasp of the data and data sources companies’ currently have access to, but also designing for the data and data sources they may be exposed to in the future, Faruqui explained.

This includes facing and navigating the “data swamp” scenario, the complex management of both enterprise and legacy data pools that must be seamlessly integrated for any real-time “smart” data application to respond as it should, Faruqui concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of BigData SV 2017(*Disclosure: Some segments on SiliconANGLE Media’s theCUBE are sponsored. Sponsors have no editorial control over content on theCUBE or SiliconANGLE.)

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