Prerequisite: None
Many companies are modernizing and improving their data management capabilities. Still, most do so with an eye on current needs rather than considering how data management will need to work in three to five years. This is a severe oversight because the key to unlocking future data management capabilities with AI depends on the foundations you're building now. As the number of data sources, complexity, and velocity continue to increase, the transformative efforts to become more agile, responsive, competitive, and innovative will strain data management programs’ ability to deliver trusted data to the enterprise.
Companies are starting today with the foundational components in data observability, data quality, and data governance that capture as much active metadata as possible while adopting their data product methodologies. Although metadata is not new, this treasure trove of data is necessary to train AI and ML models to be performant in data management functions and enable a genuine data fabric.