Research Brief: The State of DataOps Implementations

Abstract:

The demand for rapid actionable analytical insights is forcing organizations to prioritize agility, transparency, and speed across their data ecosystems. These enterprises are investing in data-driven initiatives that maximize operational efficiency, improve collaboration, and accelerate time to value. They're turning to DataOps.

Topics: data management Data Analytics

Research Brief: The Shift in DataOps Stakeholders

Abstract:

Gone are the days when the data engineer was the key persona driving DataOps. IT operations, line-of-business leaders, developers, and end-users can all claim roles in the direction of their company’s DataOps initiatives. While this cross-functional team approach to DataOps is viewed as a positive trend, the ongoing technical skills gap in key DataOps positions continues to plague most organizations, overburden stakeholders, and compromise the value of DataOps initiatives.

Topics: data management Data Analytics

Research Brief: The Value of DataOps Initiatives

Abstract:

Data quality issues, distributed data, tool proliferation, overburdened and underskilled teams, rising costs, and increased risk all contribute to the complexities of today’s data ecosystem that hinder the democratization of data and analytics. As a result, organizations are looking for ways to empower data teams to reliably deliver data and analytics to all consumers. DataOps processes liberate data silos and democratize workloads throughout the data lifecycle, yielding significant improvements in data quality, cross-functional collaboration, and analytics outcomes.

Topics: data management Data Analytics