Data Structure

Data structure in Sandbank explained simply

Sandbank adapts to your existing data structure. Storing data works with your current format.

To visualize custom data in Sandbank dashboards, custom datasets must be mapped once to the Sandbank dimensions-and-metrics schema through a guided visual flow.

This enables two important outcomes:

• Compatibility with data from different schemas
• Intuitive setup even without technical background

Integrations vs. custom data

Integrations

When a data source is connected via OAuth direct integration, no additional schema mapping is required.

Data is prepared automatically and available directly for dashboard creation.

Custom data

For API and CSV/XLSX imports, the visual editor detects common time columns automatically and guides one-time mapping into the Sandbank schema.

Alternatively, data can be uploaded already in Sandbank schema shape, so no mapping step is needed.

At least parts of the dataset must be mappable to enable visualization. Unmapped fields can still remain stored.

Scope and granularity

When connecting data sources, teams can define whether to store complete datasets or selected parts only.

Granularity is configured in the same flow and can be changed later.

Data quality

Sandbank stores data in multiple layers to make data quality checks possible.

Quality insights can be reviewed in the data area through the data quality controls.

Three simple steps to start

Step 1: Connect data automatically or upload manually

Connect data through OAuth, custom API, or manual CSV/XLSX upload.

Step 2: Store and map data

Sandbank stores data securely according to European standards. For API and CSV/XLSX imports, one-time guided schema mapping makes data available in dashboards.

Step 3: Create dashboards

Create professional dashboards with a few clicks using templates, or build full layouts manually based on your own structure.

Continue in Documentation

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