Teams often collect and prepare data broadly, without clarity on which assets truly drive GenAI performance, leading to wasted effort and critical gaps late in delivery.
To win, your GenAI solutions must be built on deliberately selected data assets that are traceable, complete, and aligned to priority use cases.
When teams lack a clear approach to target data, they struggle with:
- Unfocused data inventories: Large volumes of data are cataloged without understanding which assets create GenAI value.
- Unclear data origins and quality: Teams cannot confidently trace where data comes from or assess its reliability.
- Missed or incomplete coverage: Critical data required for GenAI use cases is identified too late or overlooked entirely.
Poor data targeting will dilute effort, increase risk, and limit the effectiveness of GenAI solutions.
In this hands-on workshop, your team systematically identifies, evaluates, and prioritizes the data assets that matter most for your GenAI use cases.
- Identify high-value data assets tied directly to GenAI outcomes.
- Categorize data based on relevance and specific use cases.
- Map data lineage and provenance to understand origins and trustworthiness.
- Prioritize data acquisition and preparation efforts.
- Validate data coverage and completeness against GenAI requirements.
Identifying High-Value Data Assets
Categorizing Data by Relevance and Use Case
Mapping Data Lineage and Provenance
Prioritizing Data Acquisition Efforts
Validating Data Coverage and Completeness
- Build a clear inventory of data assets aligned to GenAI use cases.
- Distinguish high-impact data from low-value or redundant sources.
- Understand where critical data originates and how it is produced.
- Identify missing or insufficient data early.
- Prioritize data investments that directly support GenAI delivery.
Who Should Attend:
Solution Essentials
Virtual or in-person
4 hours
Intermediate
Data inventories, lineage maps, and guided prioritization frameworks