Monthly Archives

May 2020

Azure DevOps Power BI Reporting

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Azure DevOps (ADO) is fast becoming the application lifecycle management tool of choice for modern organisations. With boards, CI/CD pipelines and Git repo capabilities, Agile practices have never been so easy to implement in project management. However, as a DevOps tool, it is understandably not designed and equipped to be a fully-fledged reporting and analytics solution as well. Luckily, Power BI can be used to integrate with ADO to deliver the kind of enterprise reporting that project managers need to properly monitor their projects. This blog post covers Azure DevOps Power BI reporting and also some examples of what kind of reporting is available.

Connecting to ADO

A connection to ADO is made possible via the OData feed option available in Power BI. Once connected, you will need to select the relevant tables to begin building a data model. For most project managers, the main objective in ADO reporting is getting clear visibility of the progress of work items. For that reason, the tables imported into the model should contain information relating to Work Items and Iterations.

Once imported, some simple transformations are required to clean the data. It is crucial that the correct relationships are created between work item tables. This is because work items in ADO are hierarchical, starting with Epics, Features, User Stories and Tasks. This hierarchical logic must be captured in the model in order for the reporting to make sense.

Once the model has been created, the report visualisations can be built. Based on experience, a clearly constructed table outlining key work item information including Sprint, Epic, Feature, User Story, Task, Assigned To, Completed Date, Task Number and Sprint Percentage is precisely what project managers want to see. Although not the most visually compelling report, these tables  clearly articulate work progress in a single view, something not easily achieved natively within ADO.

What Reporting Is Available

As mentioned previously, ADO reporting is primarily concerned with reporting on the progress of work items. However, the OData feed is able to capture most of the ADO backend, meaning that additional reporting on things such as pipelines and test results is also possible. Some typical reporting examples include:

  • Sprint progress reporting
  • Resource burndown and capacity
  • Work item cycle time
  • Work item predictability and productivity
  • Task completion forecasting
  • Work item distribution
  • CI/CD pipeline failures
  • Application testing and release results

Virtually any reporting can be custom built using Power BI and the OData feed.

Developing Power BI reporting for ADO is also useful because of its scalability. The OData feed can be re-pointed to any ADO instance, meaning that your reporting can be easily reproduced in other ADO instances. At FTS, we offer a pre-packaged report that can be easily implemented in any instance. It contains the most relevant reporting out of ADO based on our experience and has been very useful for us in managing our projects.

Finally, Power BI reports can be easily embedded back into ADO via the native web-embed functionality. A dashboard in DevOps must be first created, and include an iframe dashboard widget. Then the Power BI report can be embedded into the widget in the dashboard, thereby allowing you to view your custom reporting within the DevOps browser. This ability to embed reporting elevates ADO into being an all-in-one development management tool, greatly assisting project managers keep track of resources and progress.

If you want to begin Azure DevOps Power BI reporting, please contact us for more information.

Power BI Dataflows: New and Improved

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If you attended one of our Dashboard In A Day events earlier this year, you would have seen a brief demonstration of Power BI Dataflows, and what they can mean for an organisation. With the recent Microsoft update of Dataflows, now is a good time to familiarise yourself with this feature and learn how you can leverage it to improve the data culture in your organisation.

What Are Dataflows

If you have worked with Power BI before, then you are familiar with Power Query, which is the tool used for extracting, transforming, and loading data into a data model. Power Query allows you to connect to a variety of data sources and perform detailed transformations to manipulate data into the desired format needed to perform analysis.

Dataflows is an extension of this, in that it allows you to create these Power Query transformations and make them available across your organisations for repeatable use. This is important for two reasons:

  1. It scales data preparation, and eliminates the need for users to perform transformations again and again.
  2. It introduces a layer of governance in centralising and standardising data preparation assets.

Dataflows gives users access to clean, transformed data that they can rely on and re-use. This is vital in supporting self-service analytics in an organisation, as it provides users with the platform needed to access reliable and pre-configured data assets.

New Capabilities

Power BI has now introduced Endorsement capabilities into the Dataflows feature. Dataset endorsement capabilities have already been in use for some time and have proven very useful in establishing quality data culture in an organisation. With this capability now extended into Dataflows, quality data assets can now be more easily identified and shared across an organisation. Per the Endorsement principles, Dataflows can be marked for Promotion or Certification.

Promotion – tells users that the dataflow owner believes that this dataflow is good enough to be shared and reused. Users will need to have confidence in the dataflow owner to trust the quality of the dataflow.

Certification – tells users the dataflow has passed internal tests for quality per organisational policy. Only specified users are authorised to mark Dataflows as Certified.

Certified and Promoted Dataflows are marked with badges when users attempt to connect to them in Power BI Desktop:

This identification means that users can easily see which dataflows they should use to connect to when preparing reporting or analysis.

Why It’s Important

Endorsement is an important step in making Dataflows an enterprise-ready feature. With endorsement, an organisation must adopt a policy for reviewing and certifying data preparation assets. The introduction of this policy greatly improves the quality of data in an organisation, as only certified dataflows are being used for reporting and analytics outcomes.

Organisations that wish to promote a self-service environment will also benefit greatly from endorsed dataflows, as it reduces the need for dedicated resources to create and control data access. Instead, quality data assets can be centrally managed via Power BI and made available to the organisation to connect to and use. Users can rely on the quality of data, and do not need to perform any additional tasks to cleanse the data to get it ready for their analysis.

If you want to know how Dataflows can be used in your organisation, please contact us for more information.