Glossary

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Glossary / Evaluation and implementation guide

Data Granularity

Data granularity is the level of detail your tables capture: every individual event, or pre-aggregated summaries. Storing each email open, click and page view enables fine-grained attribution and reprocessing later.

Storing daily totals per contact is far cheaper but permanently discards detail. It is a modeling decision, distinct from storage format or retention policy, and it is hard to reverse.

A practical example

Example: a team stores only daily open counts per contact. A year later they want to know whether opens before or after 10 a.m. correlate with replies.

The raw timestamps were never saved, so the question is unanswerable without changing instrumentation.

What to evaluate before investing

  • Ask whether the platform stores raw events, aggregates, or both, and for how long.
  • Check if you can re-aggregate from raw data into new rollups without re-ingesting history.
  • Estimate storage and query cost at event level for your actual monthly volume.

Limitations and tradeoffs

Tradeoff: maximum granularity maximizes flexibility and cost. Most teams need event-level data only for key conversion actions, and aggregates elsewhere; deciding which events deserve raw storage is the real work.

Plan your next step with MeshLine

Connect this decision to your automation, organic marketing and customer lifecycle management. In a MeshLine demo, discuss your existing tools, the scope you need and how to measure the result.