To meet business needs, automation is key.
As a data or software engineer, the demand for accurate and timely data is growing, and speedy delivery is expected. You need a toolset that fits your existing skills, is easy to maintain and integrates well with open technology.
DataJoinery is cloud-based with no setup required, and built with openness at the core: Apache Iceberg for the lake, Snowflake for the warehouse and git for every change.
Generated from your conceptual model
Snowflake| Object | Type |
|---|---|
| customer_h | Hub |
| order_h, order_l | Hub and link |
| order_item_dcl | Dependent-child link |
| customer_location_l | Link between two hubs |
| employee_hl | Hierarchical link |
DataJoinery saves you time at every step.
Design the model and define the metrics that matter
The enterprise data warehouse core entities are generated, along with the data mart definitions.
Map the source data and apply business rules
The SQL tasks and data pipelines from the Iceberg data lake to the warehouse are generated automatically.
Run the pipeline, load the data, share with the right audience
Role-based and row-level security is applied, and data is shared through secure views with defined stakeholders.
Fits the skills and open tools you already use.
Everything DataJoinery generates is readable, versioned and yours, from the SQL to the documentation.
Scalable data architecture
Build a robust, scalable warehouse with Data Vault and Kimball-style modelling. Add data sources easily, with lineage and history tracked implicitly.
Always up-to-date documentation
Download user-friendly Markdown of the warehouse entities and transformation rules. Prefer code? Entity definitions and data feeds download as YAML.
Version control built in
Every change auto-commits to a git repository. SQL scripts can also be downloaded from a storage bucket you choose in AWS, GCP or Azure.
SQL generated for Snowflake
Insert-only SQL tasks are generated and pushed down to Snowflake, with modelling best practice applied for rapid development and quick delivery.
Automated tests
Unit tests check the accuracy of the data after each load. Get notified and resolve issues before anyone reports them.
Connect AI agents
Query the model, lineage, generated SQL and pipeline runs from an AI assistant through the DataJoinery MCP server, signed in with OAuth 2.1.
About DataJoinery MCP
The DataJoinery data architecture and lifecycle consolidates data into a central enterprise data warehouse: a single source of truth that makes reporting quick and easy.
How the Data Vault model is built
Start with a small use case.
Speak to a DataJoinery data specialist today.