Getting DataOps Right

Many large organizations have accumulated dozens of disconnected data sources to serve different lines of business over the years. These applications might be useful to one area of the enterprise, but they’re usually inaccessible to other data consumers in the organization. In this short report, five data industry thought leaders explore DataOps—the automated, process-oriented methodology for making clean, reliable data available to teams throughout your company.

Andy Palmer, Michael Stonebraker, Nik Bates-Haus, Liam Cleary, and Mark Marinelli use real-world examples to explain how DataOps works. DataOps is as much about changing people’s relationship to data as it is about technology, infrastructure, and process. This report provides an organizational approach to implementing this discipline in your company—including various behavioral, process, and technology changes.

Through individual essays, you’ll learn how to:

  • Move toward scalable data unification
  • Understand DataOps as a discipline
  • Explore the key principles of a DataOps ecosystem
  • Learn the key components of a DataOps ecosystem
  • Build a DataOps toolkit
  • Build a team and prepare for future trends

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