The Next Generation of Power BI Interactivity

While Power BI has delivered insights, taking action on those insights occurs in downstream processes and tools. Similarly, ad-hoc analysis often demands a more hands-on approach, requiring users to take data out of Power BI into Excel to investigate nuanced inquiries. In either case, the last mile of analytics often takes place after the reporting layer.

Now, Power BI is evolving to deliver these last-mile analytics capabilities by moving beyond a “read-only” reporting tool into an action-taking analytics tool. New capabilities in Microsoft Fabric are enabling users to conduct interactive “what-if” analysis or scenario analysis, create processes that take action, write data to data stores or conduct ad-hoc analysis with natural language while remaining within the certified analytics environment. This next evolution of Power BI will see a shift from inform to inform and act, expanding the role of the tool in analytics ecosystems.

What-if and scenario analysis

In many organisations, a centralised data team produces curated, certified datasets that fulfill many use cases, including serving as the baseline for more customised analysis. Some types of analyses, such as forecasting, greatly benefit from having up-to-date data but require manual manipulation from informed analysts to assess different scenarios and adjust business plans. Often, this analysis creates drift between the data in the source systems and the data being used to make decisions. Alternatively, local documents can be used and refreshed periodically, but this often results in multiple versions, emailed attachments, inadequate visualisations, accidental formula overrides and general concerns about data governance that are standard for any enterprise data.

There are known workarounds for some of these problems, such as using SharePoint lists or Excel documents on Teams to standardise user access and control changes to data. Protiviti has also developed workflows in concert with Power BI to provide curated data with enhanced visualisations, while enabling users to input data to see how KPIs change under certain scenarios. We have done this using Power Apps to provide user friendly write-interfaces and Power Automate to synchronise updates to underlying tables that are accessible to Power BI. While each of these methods can solve some of the initial concerns, none provide a fully Microsoft Fabric-supported solution to enable the desired type of analysis with relatively little development time.

Now, thanks to the combination of translytical task flows and user data functions in Microsoft Fabric, Power BI natively supports scenarios where users want to read data and make immediate changes to the data in the report, so that the analysis, and perhaps the resulting action, is performed within Power BI.

Rather than relying on Excel, SharePoint lists or Dataverse, Microsoft Fabric can provide easily provisioned data stores with enterprise governance controls, either through a lakehouse, warehouse or SQL database. User data functions enable SQL or python-based customised logic that interacts with these datasets in a reusable, repeatable and auditable manner. Last, Power BI and translytical task flows provide the user interface through which these data updates are made, enabling users to update specific data elements within a report, and understand the broader impacts of their adjustments on the report without worrying about creating additional copies of the certified data, recreating reports or circumventing enterprise data governance controls.

Natural language for data exploration and analysis

Business users often rely on technical analysts to translate their inquiries into the technical code that can provide an answer. Alternatively, users take provided data and analyse it in a format that they’re familiar with, such as Excel. Unfortunately, this either distances the business users from the data, or it separates the data from the curated and governed analytics environment.

Now, Copilot for Power BI is enabling users to ask questions about their reports or semantic models using natural language. Copilot works to translate the inquiry into data analysis expressions (DAX) and render back the results. This democratises the ability to analyse data using powerful query engines, while keeping the data in the governed analytics environment.

Furthering the experience of Copilot, data agents in Microsoft Fabric can supercharge Copilot, allowing data teams to build expert domain-specific agents using data from a variety of Fabric locations. These agents can be curated and customised to provide a more informed and expansive experience to end users, all while residing within the constraints of the overarching analytics environment.

Data alerting and automated actions

n Power BI, it can be helpful to set up alerts on specific metrics so individuals are notified when specific criteria are met. For example, monitoring budget to actuals or product inventory on the retail floor benefit from rapid alerting and response. Rather than requiring that users pull the report and check specific metrics, Fabric Activator can notify them right as the business condition is reported.

While some of these alerting capabilities have been supported in Power BI, Fabric Activator provides more comprehensive alerting functionality, in addition to a new suite of action-oriented capabilities that span many Fabric experiences, including Power BI. Threshold or criteria alerting can be setup in Power BI, and now Fabric Activator can trigger data pipelines or notebooks to then run a process, rather than waiting for a user to react and manually kick it off. This can significantly shorten the time from insight to action, whether pushing alerts to users so that they can restock an item, or re-running a data pipeline to grab the latest set of transactions in a store.

The next evolution of Power BI’s capabilities is elevating the user experience to cover the last mile of analytics, enabling users to perform their analysis and take the necessary action to complete the data lifecycle. Each of these different technical capabilities will broaden Power BI’s role in many analytics environments, shortening the time between insight to action.

Prashant Atri from Microsoft, also contributed to this post.

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