Power BI makes it easy to design reports of any size and for any occasion. Anything from a small internal statistics report for a team of 10, to a nationwide analysis for a company of 10,000, can be crafted intuitively and with the end user in mind. But what if we have multiple databases with millions of rows? Or we need a few different reports that all use the same data sources, but want to avoid redundancy and potential errors in querying? In these situations, it is crucial to maintain standards as much as possible to avoid data contamination, and for these issues, Power BI answers with Dataflows!

What is a Dataflow?

Dataflows are a feature within Power BI that allow you to create a group of tables that can then be cleaned and transformed, optimizing and centralizing your datasets. You can create a data table in a workspace using Power Query that can then be used and reused not only in other reports, but also by other developers. Once your data is ingested from its source (such as a database, file, or API), it is built into an entity over the Common Data Model (CDM). The CDM standardizes data structures and promotes consistency across reports, enabling you to maintain formatting and pull data quickly and cleanly.

How do Dataflows benefit you?

What makes a dataflow better to use over conventional data ingestion? There are a few main benefits:

• Creation of reusable transformation logic. Instead of the same transformations being run multiple times on the same datasets, you can design the logic once and use that every time afterwards, promoting standardization among semantic models before even entering Power BI Desktop.
• Minimized business logic. Reducing the amount of maintenance needed for your data sources as well as maintaining excellent consistency among different reports will save a lot of time.
• Promoting single source of truth architecture (SSOT). Centralizing datasets in this manner removes opportunities for human error and enables your repositories to function throughout other services within the Power Platform. With a SSOT, it is also very easy to enact changes to business logic if there is ever a need for formatting changes down the line.
• Empower security on underlying data sources. By implementing prebuilt logic, there is little need for every developer to have access to the original data. This removes vulnerabilities created by more users having access, as well as reducing load on the underlying sources.

Summary

Dataflows fill an important niche within the Power BI ecosystem: reusability. As reports become more necessary for providing valuable business insights and making data-driven decisions, having reliable datasets that are consistent among multiple reports is key. Whether you are minimizing security risks or streamlining your data pipeline for multiple reports, dataflows should be where you look. If you have more questions on using dataflows and how to choose when they are optimal, please contact us!