Power BI Deployment Pipeline: Step-by-Step Guide

Power BI is a popular business intelligence tool that helps you create interactive visual reports and dashboards to gain meaningful data insights. However, as the business grows, the amount of data for analysis increases, making the utilization of Power BI assets complex. This is where Power BI deployment pipelines can be useful. These pipelines provide a structural framework for developing, testing, and publishing business reports for end user's reference.

Here, you will learn how to create a Power BI deployment pipeline in a step-by-step manner. You can use this guide to design meaningful analytics reports for enhanced decision-making and revenue generation in your organization.

What are Power BI Deployment Pipelines?

The Power BI deployment pipeline is a feature offered by the Power BI Service (Premium License) to help you develop, test, and produce content. Power BI is one of the most extensively used BI tools, and its content includes reports, dashboards, and visualizations. The content creation process consists of three stages:

• Development: Here, you need to design, constantly review, and revise the report content in the development workspace.‍
• Test: At this stage, you can check the functionality of the content in the pre-production workspace.‍
• Production: Finally, you can consume the tested content in the Power BI workspace app or through direct access to the workspace.

A workspace is the area where you and your team create and present Power BI content. Without separate environments, you have to use the same workspace for development, testing, and production. Here, the major problem is that if you make changes to the workspace, it can create discrepancies in the testing process. The changes you made also affect the production stage, resulting in a loss of trust.

To resolve this issue, Power BI offers three workspace environments—Development, Test, and Production—according to the stages of the content creation process. Power BI deployment pipelines facilitate the effective management of these environments. You can leverage deployment pipelines in Power BI only if you have opted for a Premium or Premium Per User (PPU).

Benefits of Power BI Deployment Pipelines

Some benefits of the Power BI deployment pipeline are as follows:

• It automates the transfer of content between different workspaces. Previously, you were required to download a PBIX file and republish it to proceed to the next stage.
• You usually have to use test data when you develop a Power BI dashboard and then replace it with production data for real-world usage. Deployment pipelines automatically change data sources whenever you move from the testing stage to the production stage.

Steps To Create Power BI Deployment Pipelines

To create Power BI deployment pipelines, follow the below steps:

Step 1: Create a Deployment Pipeline

Log in to your Power BI Premium account, and click Deployment Pipelines from the left navigation bar.

Then click Create a Pipeline. Enter Pipeline Name and Description.

Step 2: Assign Your Workspace

Now, you need to assign a workspace to the deployment pipeline. Select the desired workspace from the drop-down menu. Then, choose any one of the three deployment stages for the workspace: Development, Test, and Production. Click Assign.

As a developer, you can choose the development stage. You will be redirected to the following page:

Step 3: Develop and Test Your Content

In the development stage, you can create the Power BI report by collecting relevant data from various sources. To effectively integrate data from multiple sources into a target data system, you can use a data movement tool like Airbyte. It offers a vast library of 550+ pre-built connectors. You can use any of these source connectors to extract data from several source systems and load it into the desired destination.

Some additional key features of Airbyte are:

• Flexibility to Develop Custom Connectors: Airbyte provides you with several options for building custom connectors: Connector Builder, Low Code Connector Development Kit (CDK), Python CDK, and Java CDK.
• ‍AI-powered Connector Builder: While using Airbyte, you can leverage AI assistant in the Connector Builder feature to speed up the custom connector development process. The AI assistant pre-fills the configuration fields, reducing setup time. It also provides intelligent solutions to help you fine-tune the connector configuration.
• ‍Change Data Capture (CDC): Airbyte's CDC feature allows you to incrementally capture changes made to the source data system and reflect them in the destination data system. This ensures data consistency and facilitates the creation of meaningful analytics reports.‍
• Support for Vector Databases: Airbyte supports popular vector databases, including Pinecone, Weaviate, Milvus, and Chroma. You can integrate these vector databases with LLMs to generate vector embeddings and improve outcomes of LLMs.‍
• Streamline GenAI Workflows: When using Airbyte, you can directly load semi-structured and unstructured data to vector database destinations. This enables you to manage your business organization's GenAI workflows better.

After integrating data, you may cleanse and transform it using data-cleaning techniques or transformation tools. You can then connect this standardized data from the destination system to Power BI to develop the required content.

You can now move to the test stage by clicking the Deploy to Test button. A pop-up will appear showing the content that will be copied to the test stage. Click Deploy.

On successful testing, you can transition the Power BI report to the production stage. Click on the Show More drop-down list at the bottom left side of the test stage box. A list will appear containing reports that have passed the testing process. You can select one or more reports and send them to the production stage. For example, you select the marketing analysis report. You can click on select related and select the dataset related to this report.

Then, click Deploy to Production > Deploy.

Step 4: Share With Your End-Users

After deploying the pipeline in the production stage, you will see a compare link between the test and production stage box. Click on it to see and compare the differences between these two stages.

If you want to limit the access to data used in the development and test stage, you can click the Manage Access button. Add important team members and grant each one a different permission level.

Use Cases of Power BI Deployment Pipeline

Here are some important use cases of the deployment pipelines in Power BI:

• You can utilize Power BI deployment pipelines while preparing financial reports for banks and ensure regulatory compliance. For instance, you can develop a financial dashboard that displays metrics such as interest rates for different types of loans. Using a test dataset, you can check the validity and functionality of the dashboard in the testing environment. Once validated, you can share tested content with stakeholders such as auditors. This approach helps in understanding the bank’s lending practices.
• Power BI deployment pipelines can also help monitor performance and downtime in manufacturing company production. Here, you can develop a dashboard showcasing metrics related to machinery performance. Then, you can check the accuracy of downtime calculation using a test dataset and share the results with departmental managers for corrective measures.
• You can ensure data security in Power BI while utilizing deployment pipelines by setting up an RBAC mechanism. This is critical in protecting sensitive data while analyzing patient data in the healthcare sector.

Limitations of Power BI Deployment Pipelines

You may encounter the following limitations while using Power BI to create deployment pipelines:

• You can access Power BI deployment pipelines only when you have a premium or premium per-user license.
• Before assigning a workspace for a pipeline, you must be the admin of that workspace.
• You cannot assign a workspace to multiple different pipelines.
• The Power BI deployment pipeline does not support streaming dataflow, PUSH datasets, or Excel workbooks. 

Conclusion

Power BI deployment pipelines can help manage your organizational data workflow by facilitating development, testing, and production environments for report generation. This blog explains in detail what Power BI deployment pipelines are and how to create them in a stepwise manner. You can leverage this information to deploy Power BI pipelines for effective business data analytics.