Business tables become useful when their meanings and relationships are as clear as their file formats. Start with the decision your model needs to make.
Choose the right record grain
State whether a row is an order, line item, customer event, product variant, or periodic summary. Define stable identifiers and the history needed for the task. A large row count is not sufficient when records aggregate away the events or relationships the intended workflow requires.
Document fields and relationships
Request a dictionary with definitions, units, valid categories, missing-value conventions, and time semantics. List primary and relationship keys, including composite keys and expected cardinality. Preserve distinctions between source values and derived fields so reviewers can understand how an output was constructed.
Inspect usable coverage
Review source systems, organizations, periods, and relevant category intersections. Measure key duplication, unmatched relationships, missingness, and source concentration in a pilot. Inspect whether apparent completeness comes from later updates that would not have been available at the model’s intended decision time.
Establish project-specific suitability
Bring example rows, required relationships, exclusions, and acceptance questions to Fiund. Source documentation, allowed transformations, access, sensitive fields, and delivery format should be reviewed for the actual project. Discuss the smallest representative pilot that can establish whether a source supports the intended analysis or model behavior.
Include in your inquiry
- Row grain and stable identifiers
- Field dictionary and relationship map
- Time and coverage requirements
- Sensitive-field and pilot review plan