Cloud Hosting Provider Rackspace Launches Rackspace DataOps

Multicloud technology solutions company, Rackspace Technology, has launched its Rackspace DataOps solution. The new offering expands the company’s new Rackspace Elastic Engineering model to Data. It would help clients provide trustworthy, high-quality data to business executives, data scientists, workers, partners, and apps faster.

Photo Jeff DeVerter, CTO Solutions at Rackspace Technology
“Rackspace DataOps Managed Services provide an agile and automated, process-oriented methodology combined with world-class support to improve the quality and reduce the cycle time of data analytics,” said Jeff DeVerter, CTO Solutions at Rackspace Technology.

Developing new business models and income streams, connecting with customers, getting deep insights into supply chains, and improving processes all require the appropriate data to be sent to the right application at the right time, stated Rackspace. Investing in DataOps would allow teams to quickly build and update solutions based on changing business demands by speeding up the design, development, and deployment of new data streams into the data architecture.

“83% of respondents to 451 Research’s Voice of the Enterprise (VotE): Data & Analytics, Data Management & Analytics 2020 survey stated that their company is at some stage of investment in DataOps, with more than a third having defined and established a DataOps strategy,” said Matt Aslett, Research Director for 451 Research, part of S&P Global Market Intelligence.

Sprint-Based Model

With Rackspace Elastic Engineering for Data, the core service of Rackspace DataOps, Rackspace Technology would deliver predictable delivery and change management of data, data models, and related artifacts. Rackspace Elastic Engineering for Data would provide access to a pod of data specialists via a modern managed service model that improves operational efficiency and enables innovation by offering the following:

  • ‘Do with’ Approach – Rackspace Elastic Engineering for Data pod works in an agile, sprint-based model right alongside a client’s team.
  • Consistent Team – No matter which tier of hours are used each month, users will always work with the same pod that knows them, their environment and their business.
  • Flexible, Tiered Pricing – Purchase ‘fractional access to a pod via hours-based tiers and scale up and down monthly should business needs change.
  • Multi-faceted skill sets – The Rackspace Elastic Engineering Pod for Data consists of an engagement manager, data architects and engineers working together as one unit.
  • Ongoing Innovation – Rackspace Technology leverages leading cloud platforms tools and frameworks to deliver progressive improvement, enablement and transformation.

“Rackspace DataOps Managed Services provide an agile and automated, process-oriented methodology combined with world-class support to improve the quality and reduce the cycle time of data analytics,” said Jeff DeVerter, CTO Solutions at Rackspace Technology. “This is important for our customers because it drives greater value from data by empowering business leaders with the possibilities of both live and predictive analytics from across their organization.”

Data Pipeline Management is an optional add-on service for Rackspace Elastic Engineering for Data that provides 24/7 data pipeline monitoring, management, and support.

in addition to generating more value from data, Rackspace DataOps provides sophisticated AI and machine learning capabilities that open the way to innovation, prescriptive insights, intelligent applications, and data monetization.

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