BNS DataLens
Data Modelling

Model your data, visually.

Define how your datasets relate to each other. Create joins, map keys and build a semantic layer that makes every downstream analysis faster and more reliable.

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DataLens · Dataset overview
Datasetsales_q4_2024.csv
Rows12,840
Columns24
Quality94.2% ✓
StatusWorking copy
Quality trend
How It Works

Build relationships that last

Step by step — exactly what happens under the hood.

01
Drag datasets into the canvas

Add any datasets from your workspace onto the modelling canvas. Columns are listed automatically.

02
Draw relationships

Click and drag between columns to define joins. Specify join type — inner, left, right, full outer.

03
Define keys

Mark primary and foreign keys. DataLens validates referential integrity and warns of mismatches.

04
Name your model

Give the model a name and description. It becomes a reusable asset available in the Analysis module.

05
Publish to workspace

Published models are available to all team members (Team plan). Changes are versioned.

Why It Matters

Built for real workflows

Not just a feature — a step change in how your team works with data.

Benefit 01
Single source of truth

One model definition shared across all analyses — no more conflicting join logic in different reports.

Benefit 02
Referential integrity

DataLens validates your keys and join columns before you publish — catch data model errors early.

Benefit 03
Governance foundation

Named, versioned models feed directly into the lineage graph and data dictionary.

Get Started

See it in action.

Request a demo and we'll walk you through this feature with your own data in mind.