As a Data or Software Engineer, the demand for accurate and timely data is growing. And speedy delivery is expected
To meet business needs, automation is key
Adopting a toolset that fits in with existing skills, is easy to maintain and integrates well with open technology is a must
DataJoinery saves you time, and is built with openness at the core
Cloud-based, no setup required
Quick and easy to get started.
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 are automatically generated.
Run the pipeline, load the data, share with the right audience
Role-based and row-level security is applied, data is shared via secure views with defined stakeholders.
Scalable data architecture
Build a robust and scalable data warehouse using a Data Vault and Kimball-style modelling methodology. Easily add data sources, implicitly track data lineage and history.
Low-code, always up-to-date documentation
User-friendly markdown can be downloaded to provide an overview of the enterprise data warehouse entities and transformation rules. If you prefer code, the entity definitions and data feeds can be downloaded in a YAML format.
Version-controlled
Built-in versioning with auto-commit to a git repository. SQL scripts can also be downloaded from a specified AWS, GCP, or Azure storage bucket.
Save time
SQL is auto-generated according to the target data warehouse. Snowflake and SQL Server is currently supported. Insert-only SQL tasks are used. Modelling best-practices are applied, ensuring rapid development and quick delivery of results.
Automated tests
Monitor the accuracy of the data after each load with automated unit tests. Get notified and proactively resolve issues.
The DataJoinery data architecture and lifecycle consolidates data into a central enterprise data warehouse, providing a single source of truth, and making reporting quick and easy
