What is a semantic layer in a data cleaning tool?

A semantic layer is a curated model that defines your metrics, dimensions and the everyday words people use for them. In Dotwave it ensures a term like ‘revenue’ always means the same calculation, so every chart and dashboard reports consistent numbers.

Do beginners need to set up the semantic layer?

No. Dotwave generates a semantic model automatically from your data, including sensible metrics, time hierarchies and synonyms. Beginners can use it as-is, while experts can edit and certify definitions for governance.

Semantic layer

Define your metrics once. Use them everywhere.

The semantic layer is your single source of truth for how Dotwave interprets your cleaned data. Define measures, dimensions, hierarchies, and synonyms — and every chart and NL query uses them consistently.

Real analyst problem

Your client has ‘revenue’, ‘Revenue’, ‘Rev’, and ‘total_revenue’ across different files. The semantic layer maps them all to one canonical measure — so ‘show me revenue by month’ always means the same thing, regardless of which dataset you’re querying.

Measures, dimensions, and hierarchies

Define numeric measures (revenue, units sold, profit margin) and categorical dimensions (region, product category, sales rep). Add hierarchies for drill-down (Year → Quarter → Month). Dotwave reasons over these when building charts.

Synonyms for plain-English queries

Add synonyms so ‘income’, ‘sales’, and ‘revenue’ all resolve to the same measure when someone asks a question in plain English.

Consistent across every chart

Once defined, the semantic layer applies to every chart, every NL query, and every auto-suggested visualization — not just the one you built it for.

Define your metrics once. Use them everywhere.

Measures, dimensions, and hierarchies

Synonyms for plain-English queries

Consistent across every chart

Ready to clean your data?