Choose dimensions linked to failure
Begin with the deployment setting and the distinctions most likely to affect performance. For extraction that may mean layout and language; for forecasting it may mean time and business cycle. Avoid adding demographic or organizational details that the task does not require and the source cannot substantiate.
Count intersections, not just totals
A collection can contain several languages and several industries while offering only one industry in each language. Request a cross-tabulation of the critical combinations. Distinguish unavailable cells from unknown metadata, and record how many independent organizations or templates contribute to each meaningful slice.
Expose concentrated sources
Track the share of records contributed by the largest organizations, templates, or periods. A large headline count can be dominated by one recurring report format. Use sample inspection to determine whether apparent diversity represents substantive process differences or repeated exports of essentially the same records.
Set priorities before sourcing
Rank required coverage, useful additions, and acceptable gaps. Explain whether a small balanced pilot is more useful than a larger concentrated batch. Share that matrix with Fiund so feasibility discussions focus on the combinations that matter, with source suitability and permitted scope reviewed for each proposed collection. Imagine a request covering invoices in three languages across four sectors. A useful matrix shows each of the twelve combinations, even when some contain no records. That view makes tradeoffs explicit and prevents separate language totals and sector totals from implying combinations that the proposed source does not actually contain.
Review checklist
- Select task-relevant coverage dimensions
- Request important intersection counts
- Measure source concentration
- Rank mandatory and optional coverage