As more organizations invest in dataops, data governance, and data security, metrics that measure the value, operational efficacy, and risk involved are crucial. Related content.

Putting the “Ops” in DataOps: Success Factors for Operationalizing Data, a recent report from BMC in partnership with 451 Research and S&P Global, found that defining a successful DataOps ...

Concurrent with the rapidly evolving digital landscape, enterprise data management is poised for transformative change in the coming years. At the same time, organizations driven by exponential data ...

From misclassified data to AI use without adequate quality assurance, IT leaders looking to make the most of data-driven ...

DataOps and data governance are tightly interwoven and, as such, continue to grow in importance. The dangers of ‘dark’ data. It all comes down to data quality. The downstream effects of data quality ...

Once you lay the foundation for data governance, Thompson said, there are many operational things you can begin to do, including building policy, whether it be data security, dataops or something ...

DataOps brings together IT data owners, database administrators, ... regulations and governance. Through DataOps, IT can clearly explain why current limits are in place, ...

Providing actionable insights through analytics requires a strong dataops program for integrating data and a proactive data governance program to address data quality, privacy, policies, and security.

The most relevant Big Data trends for South Africa will centre on the familiar themes of cloud adoption and data platform readiness, the maturation of artificial intelligence (AI) models into ...