Rethinking Data Governance: Metrics for Meaningful Outcomes
Data governance has been obsessed with a metric that feels more like accounting than strategic decision-making: coverage. The problem? Coverage misses the mark.
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For years, data governance has been obsessed with a metric that feels more like accounting than strategic decision-making: coverage. Data Governance tool vendors educated a generation of governance professionals to diligently track the percentage of documented data, chasing a completion checkbox that often misses the bigger picture.
The problem? Coverage misses the mark. It assumes that meticulously documented data automatically translates to understandable, usable information. But what if the end user just needs an answer to a question? Why make them navigate a labyrinth of tables, columns and descriptions when the goal is simply to get the right information, quickly and efficiently?
Counting beans doesn't answer questions. While documentation is valuable, it's merely a means to an end. The real goal? Empowering users to find the information they need to make informed decisions. Chasing coverage metrics often misses this mark, creating a documentation burden while neglecting the user experience.
This is where GenAI offers a glimpse into a future of data governance focused on outcomes, not just outputs. Imagine a system that understands context, piecing together relevant information from diverse sources — documents, Slack conversations, even table/column descriptions — to deliver meaningful answers to user questions, regardless of their location or formatting.
Suddenly, governance shifts from bean counting to outcome-driven. Instead of chasing arbitrary documentation goals, we'd focus on empowering users with intuitive access to the information they need.
Here's how it works:
- Contextual Understanding: GenAI analyzes user questions and the surrounding context, identifying relevant data sources beyond just documented tables.
- Information Fusion: Instead of siloed data, GenAI would seamlessly combine information from documents, conversations, and other sources, creating a unified knowledge base.
- Frictionless Access: Users wouldn't need to know the exact location or format of the information they need. GenAI would handle the search and retrieval, delivering the answer in a clear, actionable format.
This reframing unlocks new possibilities:
- Reduced Documentation Burden: Teams focus on creating quality information, not filling quotas.
- Improved User Experience: Users find the answers they need, where they need them, without chasing through data dictionaries.
- Smarter Data Utilization: GenAI extracts hidden insights, leading to improved decisions and innovation.
- Dynamic Knowledge Management: Information stays relevant, automatically adapting to changing contexts and assumptions.
Adopting GenAI-powered data governance isn't about throwing away existing practices, but about evolving them to focus on what truly matters: empowering users with the information they need to thrive. It's time to move beyond counting beans and embrace a future where data governance delivers real value by driving meaningful outcomes, not just checklists.
Published at DZone with permission of Kirit Basu. See the original article here.
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