Lume

Connect to the customer's ERP system (e.g., SAP, Oracle).

Lume automatically discovers the schemas and data relationships.

AI suggests mappings to your data model, which you review and approve.

Lume generates dbt code to transform the data into your standard format.

Deploy the transformations to your data warehouse.

Connect to the legacy database using Lume's connectors.

Lume handles complex joins, nested data, and outdated schemas.

AI-powered data mapping suggests transformations to align with your data model.

Collaborate with the customer to approve data definitions.

Generate and deploy dbt code for data transformation.

Connect to customer's data source (e.g., CSV file, database dump).

Lume analyzes the data and suggests data cleansing and normalization rules.

Review and approve the suggested transformations.

Lume generates dbt models to apply the transformations.

Deploy the normalized data to your data warehouse.

Invite the customer to the Lume collaboration portal.

Share the proposed data mappings and transformations with the customer.

The customer reviews and approves the data definitions.

Track the customer's progress and approvals within the portal.

Generate and deploy the transformations based on the approved definitions.

Configure data quality checks within the Lume platform (e.g., null checks, range checks).

Lume automatically runs these checks on the incoming data.

Alerts are generated if any anomalies or quality issues are detected.

Investigate and resolve the identified issues.

Redeploy the data with the corrections.