Proper planning and governance are critical to ensure the effective use of Power BI, maintain data integrity, and comply with organizational standards and regulations. Here are a few key areas which can assist in your Dev Ops strategy.

Define Objectives and Requirements

• Business Objectives: Clearly define the business objectives and key performance indicators (KPIs) that Power BI will address.
• Stakeholder Involvement: Engage stakeholders from various departments to gather requirements and ensure the solution meets their needs.

Data Strategy

• Data Sources: Identify and document all data sources that will be used in Power BI reports.
• Data Quality: Implement processes for ensuring data quality, including data cleansing and validation routines.
• Naming Conventions: Standardize naming conventions for datasets, reports, and dashboards to maintain clarity and consistency.
• Coding Standards: Establish coding standards for DAX and M queries.

Architecture Design

• Data Modeling: Create a robust data model that supports the required analysis and reporting needs. Use star schema or snowflake schema for efficient data organization.
• Environment Setup: Plan for development, testing, and production environments to facilitate proper development workflows and quality assurance.

Data Governance

• Data Ownership: Define data owners and stewards responsible for the accuracy and integrity of data.
• Data Catalog: Maintain a data catalog to document data sources, datasets, and their relationships.

Security and Compliance

• Access Control: Implement role-based access control (RBAC) to ensure that users have appropriate permissions based on their roles.
• Data Sensitivity: Classify data based on sensitivity and implement measures to protect sensitive data, such as encryption and masking.

Content Governance

• Version Control: Use version control systems to track changes to Power BI reports and datasets.
• Approval Workflows: Implement approval workflows for publishing and updating reports to ensure quality and consistency.

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Power BI Desktop introduces a new way to author, collaborate, and save your projects. When you save your work as a Power BI Project (PBIP), report and semantic model item definitions are saved as individual plain text files in a simple, intuitive folder structure.

Saving your work as a project has the following benefits:

• Text editor support - Item definition files are JSON formatted text files containing semantic model and report metadata. They're publicly documented and human readable. While project files support simple text editing tools like Notepad, it's better to use a code editor like Visual Studio Code (VS Code), which provides a rich editing experience including intellisense, validation, and Git integration.
• Programmatic generation and editing item definitions - You can create scripts using the popular and easy to use Tabular Model Scripting Language (TMSL) , or create your own custom applications to make changes to your item definitions. Applications can be based on public documentation of the item definition schemas and/or client libraries.
• Source control - Power BI semantic model and report item definitions can be stored in a source control system, like Git. With Git, you can track version history, compare revisions (diff), and revert to previous versions. Source control can also unblock collaboration when using Power BI Desktop by using familiar collaboration mechanisms for resolving conflicts (merge) and reviewing changes (pull requests). To learn more, see Version control in Git.
• Continuous Integration and Continuous Delivery (CI/CD) - You can use systems where developers in your organization submit a proposed change to the CI/CD system. The system then validates the change with a series of quality gates before applying the change to the production system. These quality gates can include code reviews by other developers, automated testing, and automated build to validate the integrity of the changes. CI/CD systems are typically built on top of existing source control systems. To learn more, see DevOps - Continuous integration, and DevOps - Continuous delivery.

Microsoft Documentation: https://learn.microsoft.com/en-us/power-bi/developer/projects/projects-overview

Non-Affiliated Blog Post: https://powerbi.microsoft.com/en-us/blog/deep-dive-into-power-bi-desktop-developer-mode-preview/

Power BI deployment pipelines facilitate the development, testing, and deployment of reports and datasets across different environments. Properly managing these pipelines ensures efficient workflows, consistency, and high-quality outputs.

If you have Power BI Premium (or Premium Per User) then you can make use of Power BI Deployment Pipelines, which are a huge step forward in release management.

Your developers work in a (Premium) development workspace, we recommend looking into Premium Per User for this, to help reduce the workload on your production Premium capacity.

Then their changes can be deployed into a (Premium) testing workspace, once it has been tested and approved then the changes can be deployed into a (Premium) production workspace.

This provides structure and incremental promotion of changes through the release process. It manages the promotion of multiple items in one go (reports, datasets, etc.) and you can even configure parameter values so that different dataset parameters are automatically applied in the promotion process; which enables you to configure different data sources or Power Query filters in different environments.

However, it is not perfect:

• All three workspaces have to be Premium (or Premium Per User)
• Sensitivity Labels are not supported
• You lose the ability to download the PBIX following deployment
• There is no source control, version control, or rollback

Find out more at https://docs.microsoft.com/en-us/power-bi/create-reports/deployment-pipelines-overview

Utilizing Azure DevOps, users can setup systems where developers submit a proposed change to the CI/CD system, and the system subjects the change to a series of quality gates before applying the change to the production system. The quality gates may include things like reviews by other developers (code review) and automated testing.

Continuous integration (CI) is the process of automatically building and testing code every time a team member commits code changes to version control. A code commit to the main or trunk branch of a shared repository triggers the automated build system to build, test, and validate the full branch. CI encourages developers to share their code and unit tests by merging their changes into the shared version control repository every time they complete a task.

Continuous delivery (CD) is the process of automating build, test, configuration, and deployment from a build to a production environment. A release pipeline can create multiple testing or staging environments to automate infrastructure creation and deploy new builds. Successive environments support progressively longer-running integration, load, and user acceptance testing activities.

Version Control System (VCS): Using a Version Control System like Git to track changes and manage versions of Power BI artifacts is a useful and effective practice of disaster recovery, and allows rollback of individual changes to a Power BI report or dataset.

Utilize PBIP alongside GIT version control to collaborate on datasets and reports with other users across your business.
Implement a branching strategy (e.g., GitFlow) to manage development, staging, and production environments.

A VCS is extremely useful, but also requires a technical understanding of Git and other advanced toolsets to get it configured and working. And most business users must go through a developer or DBA to restore these backups.

This is where Power BI Sentinel can help! We provide a simple and intuitive change tracking solution that provides detailed comparisons of your reports and any changes that have occurred.
More Information: https://www.powerbisentinel.com/change-tracking/

Power BI Sentinel's change tracking functionality can be used across a wider audience with minimal technical knowledge to operate. Note that Power BI Sentinels version control and rollbacks can only be done at the report level, and individual changes cannot be rolled back. This is where combining Git and Power BI Sentinel may provide a much more comprehensive solution across your entire organization.

Other good practices for Version control include:
Repository Organization - Organize repositories to separate different projects and environments.
Commit Messages - Use descriptive commit messages to track changes effectively.

Auditing

Monitor usage metrics to understand user interaction and report performance. Use this information to inform decisions on new report development, or removing unused artefacts.

Power BI Sentinel can give you full oversight of user actions, report usage and methods of consumption across your entire tenant.

More information: https://www.powerbisentinel.com/usage-logging/

Implementing methodologies for optimizing data models, DAX queries, and report visuals for better performance.

Finding out this information using Power BI can be tricky or near impossible without a premium subscription.

Power BI Sentinel can provide you full logs of your data refresh performance, schedule and failures. See all of your failure information including times, dates, # of refresh attempts and error messages.

Security and Compliance

Ensure data is encrypted both in transit and at rest. This ensures that there is minimal risk in both data transfer, where any data intercepted in transfer would be meaningless without the decryption key. And where data is in storage, so that anyone who gains access to your systems will be unable to read sensitive data.

Conduct regular compliance audits to adhere to regulatory requirements by providing details logs, and compliance metrics from your estate. With native power bi logs, this maybe a long and complex task. But with Power BI Sentinel, full compliance reports can be just a few clicks away.

Provide full lists of permissions data from across your entire tenant, show which workspaces can be accessed by who, with individual access levels, plus apps and security group detail.

Show detail endorsement information from your datasets, to show where you use RLS, sensitivity labels or promoted datasets.

Alongside these tenant wide reports, Power BI Sentinel also provides full and comprehensive documentation exports of your reports and datasets. View lists of measures and calculated columns, dataset relationships, cardinality and schemas. See full Mquery readouts, and a list of used and unused columns from your datasets. All exporatble by HTML or PDF document for your compliance reporting.

More Information: https://www.powerbisentinel.com/documentation/