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Report details
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24
Figures
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0
Tables
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Executive Summary
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Introduction
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Research Findings
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Overarching Data Strategies Continue to Emphasize the Importance of Trust in…
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Organizations Are Looking to Increase DataOps Spending with a Goal of Overcoming…
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The Criticality of Automation and Data Observability Cannot Be Overstated When…
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Data Integration Continues to Serve as a Lynchpin to DataOps
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Data Engineers Continue to Be Critical to DataOps, but It’s Increasingly about…
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DataOps Done Right Delivers Undeniable Benefits that Include Increased Employee…
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Conclusion
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Research Methodology
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Respondent Demographics
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ESG Research Report: The State of DataOps
Aug 25, 2022
by
Bill Lundell
The need for rapid insight is forcing organizations to prioritize agility, transparency, and speed across their data ecosystems with a goal of improving operational efficiency, improving collaboration, and accelerating time to value from investments in support of data-driven initiatives. But organizations need help ensuring seamless orchestration, appropriate management, and timely delivery of data in support of the people, tools, processes, and environments that fuel their business. Between data quality issues, distributed data, tool proliferation, overburdened and under-skilled teams, rising costs, and increased risk, the complexity of today’s data ecosystem hinders democratization of data and analytics. This is a big reason why organizations are turning to DataOps—an agile, automated, and process-oriented methodology used by data stakeholders to improve the quality, delivery, and management of data and analytics. And the wide belief is that establishing DataOps will set organizations up for success as they look to achieve a data-driven future through an agile, process-oriented approach to securely accessing and analyzing data at scale.
Page Count: 27
Table of Contents
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Executive Summary
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Introduction
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Research Findings
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Overarching Data Strategies Continue to Emphasize the Importance of Trust in Data Platforms, Processes, People, and Data Itself
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Organizations Are Looking to Increase DataOps Spending with a Goal of Overcoming Both Business and Technical Challenges
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The Criticality of Automation and Data Observability Cannot Be Overstated When It Comes to DataOps Effectiveness and Success
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Data Integration Continues to Serve as a Lynchpin to DataOps
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Data Engineers Continue to Be Critical to DataOps, but It’s Increasingly about the Other Personas
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DataOps Done Right Delivers Undeniable Benefits that Include Increased Employee Data Access and Improved Effectiveness for Data Producers and Consumers Alike
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Conclusion
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Research Methodology
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Respondent Demographics
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