Skip to content

StromFLIX/modern-data-warehouse-dataops

 
 

Repository files navigation

page_type languages products description
sample
python
csharp
typeScript
bicep
azure
azure-data-factory
azure-databricks
azure-stream-analytics
azure-data-lake-gen2
azure-functions
azure-data-share
Code samples showcasing how to apply DevOps concepts to the Modern Data Warehouse Architecture leveraging different Azure Data Technologies.

DataOps for the Modern Data Warehouse

This repository contains numerous code samples and artifacts on how to apply DevOps principles to data pipelines built according to the Modern Data Warehouse (MDW) architectural pattern on Microsoft Azure.

The samples are either focused on a single azure service (Single Tech Samples) or showcases an end to end data pipeline solution as a reference implementation (End to End Samples). Each sample contains code and artifacts relating one or more of the following

  • Infrastructure as Code (IaC)
  • Build and Release Pipelines (CI/CD)
  • Testing
  • Observability / Monitoring

Single Technology Samples

End to End samples

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

About

DataOps for the Modern Data Warehouse on Microsoft Azure. https://aka.ms/mdw-dataops.

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Shell 33.3%
  • Python 19.7%
  • Jupyter Notebook 10.2%
  • HCL 8.8%
  • PowerShell 8.3%
  • Bicep 6.5%
  • Other 13.2%