It's important to learn how to embrace Azure DevOps for Data & Analytics workloads
In this course we learn you how to embrace Azure DevOps for Data Analytics. This course highlights the principles of DevOps including what is CICD, what is infrastructure-as-code, what is git, what is a pull request, etc but also has hands-on exercises using git, Azure Pipelines, Infrastructure-as-code using ARM and use of DevOps within Azure Data Factory and Azure Databricks. This course is not focused on teaching agile of scrum methodology but rather to 'how to practically do it for BI & Anaytics using Azure DevOps'
After this course, you will know all basics on how to use Azure DevOps for your Azure BI or Analytics environment.
This training is a 1-day training covering Azure DevOps. We'll cover the following topics
- Azure DevOps set-up & configuration
- Projects, teams, link with Active Directory
- When to use one vs. multiple projects and repositories
- Service principals and build-machine
- Role of Azure Key Vault for DevOps
- Overview of Azure DevOps components incl. Boards, Repo, Pipelines, Artifacts
- Use of Azure Boards for backlog, sprint planning and the link with development
- Use of git for version control and use of Azure Pipelines
- Within Azure Data Factory and Synapse
- Within Databricks using Workspace 2.0
- Use of pull request, review & release management across Dev, Test and Production
- Infrastructure-as-code using ARM templates and/or Terraform
- Use of artifacts as package repository
- You are a BI manager, Data manager, Architect or developer (i.e. BI analyst, Data Engineer or Data Scientist) interested in the cloud for data & analytic workloads
- You know at least the basics of agile and scrum methodology
- You are familiar with the basics of Data & Analytics in Azure - e.g. by following the Azure fundamentals for Data professionals-course
- € 625 per day
Interested to know more?
For more information, please reach out email@example.com and we can give you more details & practicals.
The full element61 Training schedule (incl. when which training runs) can be found here.
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