Prerequisite: None
Data governance often focuses on "defensive" issues involved in protecting sensitive data and adhering to laws, rules, and regulations—and rightly so, given the risks and potential penalties. However, the "offensive" side of data governance, which focuses on data quality, is also vital. TDWI research shows that delays and difficulties in carrying out curation steps for improving data quality, validity, integrity, and authenticity are top issues preventing organizations from achieving business value with data.
Organizations need excellence and efficiency in both types of data governance to establish trust in data and successfully develop data products. With pressures escalating to increase data-driven decisions and deploy analytics and AI, organizations must modernize practices and technologies for improving data quality and ensuring timely and appropriate data preparation.
This session will discuss TDWI perspectives on trends shaping how organizations can improve data trust through better integration of offensive and defensive data governance. Topics to be covered will include:
- The importance of data stewardship for addressing data trust challenges
- Trends in using data catalogs and related data intelligence systems for offensive and defensive data governance
- How AI-driven automation is shaping the future of data governance in data integration and data pipelines