What is the difference between data governance and data stewardship?  As the title of this post would imply, stewardship is a tactical function. And by tactical I mean short-term, specific, and local.   The common thread here is that these tasks all are executed against specific business terms or data elements.  Examples of tactical data stewardship tasks

Implementing a Data Governance (DG) program is all about changing the culture of the enterprise. Data Governance uses principles of accountability, integrity, and transparency to tear down silos and build trust in the data, trust that the business needs of individuals are met, and trust that top quality data is being used to make the

Data quality and data governance just don’t get any love in the big data world. Compared with all of the technology innovations in Business Intelligence (real-time dashboards, mobile BI, advanced visualization), data warehousing (MPP architectures, in-memory computing, data virtualization), and advanced analytics (in-database analytics, Hadoop, NoSQL), poor old data quality just doesn’t seem exciting.  But

The Data Management Association (DAMA) is now offering a Data Governance Certification as an option of their current Certified Data Management Professional, which is a natural extension since the test for Data Governance already existed under their current certification process and merely requires a specific configuration of test modules.  But what does Data Governance certification

Data Quality / Governance The data quality/data governance challenge is how to ensure that the business-critical decisions being made can be accomplished with high enough confidence that you can move from data governance to the realm of decision governance (i.e. all decisions are made with the best available information; we are acting on what and