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 organizations are turning to DataOps.
DataOps is 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.
In order to gain more insight into these trends, ESG surveyed 403 technical and business data professionals at organizations in North America (US and Canada) involved in data and analytics strategy with knowledge of modern tooling, technology, and processes. This research aimed to assess the state of DataOps, including market maturity, experienced challenges, factors influencing buying and planning decisions, and business benefits.
A few key findings:
