Microsoft – Page 16 – STL

Microsoft has created interesting and engaging AI (Artificial Intelligence) visuals for Power BI. The desktop app offers four AI visuals – Q&A, Key Influencers, Decomposition Tree, and Smart Narrative. This is Power BI AI Visuals Part 3 – Decomposition Tree, the third in a series which looks at all four AI visuals.

AI visuals are extremely useful. All four visuals can provide your report with insights and information from your data model, without which you will have to do DAX measures to create your own visuals.

The Decomposition Tree visual

The Decomposition Tree visual in Power BI Desktop can let you visualize data across multiple tables and columns from your data model’s multiple dimensions. It automatically combines data and supports drilling down into multiple dimensions in any order. This tool is beneficial for ad hoc evaluation and managing root cause analysis.

In the example below, we used the Decomposition Tree visual to explore the employees’ productivity score. Productivity is measured frequently in the company, and we are using the visual to explain the score on many dimensions of the data model.

The Process

To create a decomposition tree visual, click Decomposition Tree on the Insert tab in the AI Visuals group. Then add the column you would like to investigate to the Analyse box for the visual. Here, you can drag the productivity score to the Analyse box and click on the down arrow in the box. This changes the calculation from Sum to Average.

Below you can see the start of the decomposition tree.

To investigate the score by department, we added the department column to the Explain By box. Have a look at the result of this action below.

Now the Decomposition Tree visual has broken down the average productivity score by department.

Below, we added the hierarchy dimension to the Explain By field. As you can see, it explains the productivity score by the department with the highest score. In this example, it is the finance department.

The audience can, however, interact with the graphic to investigate the other departments. To do this, simply click on a different department in the Decomposition Tree visual. Below, we selected the production department.

In the Decomposition Tree visual below, we are investigating the average number of sick days for the year 2019 (slicers can also filter the result in the Decomposition Tree visual). The result is broken down from highest to lowest score in an engagement survey this company does regularly to measure the employees’ job satisfaction. It may surprise you that employees with a high satisfaction score have a higher number of days of sickness.

The Decomposition Tree visual also shows the data broken down by Department and Hierarchy.

Conclusion

That concludes Power BI AI Visuals Part 3 – Decomposition Tree. This visual is a smart and efficient way to show and analyse multiple dimensions of your data model. You get in-depth knowledge from your data sets without having to use complex DAX measures.

This is part 3 of a series of four as mentioned at the top. If you would like to learn about the other AI visuals in Power BI, please follow STL on LinkedIn or visit our website.

STL has two Power BI courses which include AI visuals. Power BI Reporting and Power BI Modelling, Visualisation and Publishing.

Microsoft has created some interesting AI (Artificial Intelligence) visuals for Power BI. Power BI offers four AI visuals – Q&A, Key Influencers, Decomposition Tree, and Smart Narrative. This is Power BI AI Visuals Part 2 – Key Influencers.

AI visuals are extremely useful and all four can provide your report with insight information from your data model. Without these, you have to do DAX measures and create your own visuals.

Key Influencers visual

We used the same HR data model in the entire four-part series ‘Artificial Intelligence Visuals in Power BI Desktop’. In this blog post, we explain the Key Influencers visual. The HR data model measures the employees’ engagement score, number of sick days, and the employees’ productivity.

The report needs to visualise the key influencers for high engagement, high productivity, and why someone has many sick days.

To do this, some decisions have to be made. You will have to define what a high engagement score is, what a high number of sick days is, and what a high productivity score is.

The Method

If you decide that more than 5 days a year is a high number of sick days, you will need a calculated column where you test the number of days an employee has been sick. The calculated column could look like this: High/Low # of days sick=If([Days of sickness]>5, “high”,”Low”). We need to use the same logic for engagement and productivity.

To get the Key Influencers visual, click Key Influencers on the Insert tab in the AI visuals group.

The Results

In the example below, we added the logical column to the Analyse field in the visual. At the top, we selected High, because the key influencers for many days of sickness need to be found.

Below, we have dragged the information about the employees’ gender to Explain By. As you can see, the employees’ gender is not a key influencer for high level of sickness.

Below we have added four more columns to Explain By: Department, Part/Full Time, Title, and Hire Date. The Key Influencers visual now explains that the top influencer for a high number of days sick is Title. If you are a general employee in this company, the chances of having a high number of sick days are 6.2 times higher than other titles. The second largest influencer is an interesting one. It is Hire Date. All employees hired from the 22 January 2015 to 6 August 2015 have a 3.1 times greater chance to have more sick days.

Below, High has been changed to Low to show the key influencers for a low number of sick days.

Within the Key Influencers visual, each key influencer can be visualised with a chart inside the visual. Above, you can see the chart for the top influencer. If you want a key influencer visualised in the chart, you just need to click on the circle with the number.

Below, we clicked on the circle with the number 1.32x to see the chart for Part/Full time

Below, you can see the visual showing the key influencers for Low productivity.

The last image shows the key influencers for a high engagement score.

Conclusion

The Key Influencers visual can give you very surprising insights from your data model. You can cross-analyse many data sources. This will give you an understanding of correlations and variables which influence your company’s results negatively and positively. Such insights can help you make decisions which will increase profitability. The Key Influencers visual can make in-depth analysis of your data sets much quicker.

This concludes Power BI AI Visuals Part 2 – Key Influencers. If you want to learn about the remaining two AI visuals in Power BI, please follow STL on LinkedIn or visit our website.

STL has two Power BI courses which include AI visuals. Power BI Reporting and Power BI Modelling, Visualisation and Publishing.

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