One of our experts had previously produced a meaningful report of Finland’s Corona data. Now, after the launch of Microsoft’s new SaaS offering called Fabric, we will test its reporting feature which is supposed to ease the work of Data analysts and BI developers. With the “Auto-create report” -feature embedded to MS Fabric you can create insights from datasets with just one click. In the following text, we are going to compare the reports built by Fabric and our expert, and review if the quality of auto-created report matches the one produced by an expert.
Fabric’s auto-created report of Finland’s Corona data
How does it work?
From Fabric UI you can conveniently access your data. You are able to create datasets from the files and tables you have uploaded to OneLake, which is this new unified data source we discussed in the previous blog concerning MS Fabric. By selecting the dataset you would like to create the report of, you can decide whether you like to build the report from scratch or if you want the Fabric to automatically build the report.
When you decide to automatically create the report, Fabric picks up the columns from the tables it thinks are the most meaningful and creates the visuals to reflect the insights of that data. It creates a quick summary page to show the most important highlights on its opinion. It also writes a short text to summarize the insights of the visuals. You can then change the data you want to be projected and it automatically builds new visuals of the selected data.
Comparison
Using the “Auto-create report” -feature you can easily build a sufficient report which tells effectively the key insights of the data. You probably still need to do some work selecting the right data to be projected, because it doesn’t necessarily pick up the right columns right away. The report it creates, may be good enough, if you just need to quickly check what is happening. However, the report it creates, isn’t visually as exquisite or informative as one created by an expert. Also, it only offers a quick summary of the data, whereas a human can create multi page report offering deep understanding of the matter. You can also change the type of the visualizations in the automatically created report, but it is as simple to build the report from scratch. If you want to build a presentable report with the help of “auto-create report” -feature, you have to put as much thought and effort on it as if you were to build the whole thing from scratch.
In conclusion, we think that this feature is nice add to Power BI, because anyone can easily check the insights that the data has to offer and make decisions based on that information. Anyway, if you want to create a report that offers powerful support for your presentation, you still need to use some time on building the report and empathizing the major data points.
Future of AI Analytics
Even though the quality of the automatically created report isn’t yet quite as insightful as the report created by human expert, it still is impressive, how well it can connect different types of data and produce meaningful visuals all by itself. AI and machine learning technologies have been rapidly evolving in recent years and Data Analytics offers great usage for those. They are already great at identyfying patterns and analyzing the relationships and dependencies between variables. Therefore, we believe that there is still room for this “auto-create report” -feature to improve. In the future, it might be able to interpret and communicate the information hidden in the data even better than the brightest expert.
At the moment, the trend seems to be that we are trying to advantage AI by using generative AI language models as a trusted helper that will do the hand-on work for us. Microsoft has informed us about the copilot feature which will be included in the Fabric offering but isn’t available yet in the public preview version. They have showed us how you’ll be able chat and tell what information you want to know from the data. It can create measures and SQL views. Of course, it can create visuals, but it can answer more sophisticated questions too. For example, it can show you with visuals the reasons why something has happened or give suggestions via chat on how you could improve certain values. With the copilot, the only thing left for humans to do, is to know what to ask. Often those questions repeat themselves so maybe we might be able to automate also that task someday.
