The Q&A Visual In Power BI

This article is for Power BI beginners & intermediates who already understand what Power BI is and who are looking to learn how to use the Q&A visual.

The Q&A visual in Power BI allows you to create visuals using Power BI’s natural language processing engine to interpret your question and get an answer from your data.

Half of business intelligence is analysing your data the other half is learning the best way to present your data using Power BI. We cover both on our Power BI courses.

When Should I Use a Power BI Q&A Visual?

The Q&A visual is most valuable when you are looking to produce something quickly.

It is perfect when trying things out or exploring as it allows you to develop multiple visuals very quickly, just as Power BI’s automated machine learning capabilities allow you to experiment with multiple data models very quickly.

If you are looking for inspiration, they work very well as Power BI will suggest both the types of data to use in your visual and the type of visual itself.

Another good use case is if you are going to be asked questions about your data which you will be expected to answer in real-time.

Instead of building a visual for every possible question, the Q&A visual allows users to ask and answer their own questions interactively.

Another visual that is useful in this scenario is the tree decomposition visual.

Keep in mind that the Q&A visual works best when your data is prepared, with all fields in plain language. If your fields are not set up this way, creating a Q&A visual is more cumbersome for the person asking the question.

Creating a Power BI Q&A Visual Step-By-Step

Adding a Q&A visual is very simple.

In Power BI Desktop, navigate to your Visualisations pane and search for the icon that looks like a speech bubble.

Finding The Q&A Visual


Adding this visual to your report will review your data and suggest some questions for you.

You can either create your own question by typing in the “Ask a question about your data” box or clicking on the pre-made questions below. The Q&A visual can also present more question options by selecting “Show all suggestions” at the bottom.

The beauty of natural language processing works is that the Q&A visual can understand complete sentences or shorter phrases containing just the keywords.

As you begin to type your questions, Power BI creates suggestions based on your data to make it even easier. Fields that Power BI recognises will be underlined in blue. Words Power BI doesn’t recognise will be underlined in red.

Typing A Question In Q&A Visual

In this example, the Q&A visual also suggests the best way to present the data is a horizontal bar chart.

Suggested Visual For A Question

If the chart that Power BI creates for you does not look right, you can also define the type of visual you want. You can specify the type of chart you want by adding “as a” and the type of visual to the end of any question.

Image of a map visual


The Q&A visual can recognise a variety of types of keywords, such as aggregates (sum, total, highest lowest), comparisons (vs, compared to), and dates, to name a few options. For a complete listing of possible keywords, you can refer to the information here.

Freezing A Q&A Visual

Once you have a visual that you want to keep for your Power BI report, you can convert it into a standard visual by clicking on the button in the top right of the visual.

Freezing A Q&A Visual

After converting the visual, you can make any of the usual alterations to a visual’s formatting, for example, using a theme to standardise your presentation.

Using “Teach Q&A”

The “Teach Q&A” feature allows you to enter terms that Power BI’s natural language processing engine doesn’t understand and show it how to relate them to your data.

Depending on your organisation and how you operate, there may be different phrasing people use. One example is geographic boundaries.

In some cases, it could be “State”, in others “Province”, or something else entirely.

This feature is accessed by clicking on the gear icon in the top right of the visual.

Accessing Teach Q and A

Once inside the setup menu, you will have several different options.

Teach Q&A Options

1. Field synonyms

Field synonyms allow you to manually adjust which words Power BI understands to mean the same thing.

So using our example above, you can update Power BI to understand that “State” and “Province” are being used to mean the same thing.

You can add or remove terms and even turn on or off the synonyms for a field.

The Q&A visual automatically creates synonyms based on the common terms.

2. Review questions

Review questions give you the ability to see what questions users have asked. This can help improve the accuracy of Q&A by tweaking synonyms or changing what your fields are called.

The review questions feature requires an enterprise subscription to work. This article gives more detail on the different Power BI subscriptions.

In this example, “person” was used, which isn’t in the data fields or the synonyms.

Power BI can create the visual by updating Power BI’s language processing engine to know “person” actually refers to “employee”.

Using Review Questions

3. Suggest Questions

Suggest questions allow you to pre-populate the suggested questions for the visual. This can be helpful if you review questions users are asking most often and put the top questions in the list or include questions users are asking incorrectly.

Final Thoughts

The Q&A visual can be a powerful tool, but it must be used for the right job like all tools.

It isn’t something that you will want to have on every report and can quickly become overused.

Just as you might work to speed up Power BI, this is a way to speed up your report development or find inspiration for your visuals.

Articles On Other Power BI Visuals

Creating Combo Charts In Power BI

The Word Cloud Visual

Creating A Bullet Chart In Power BI

Creating Scatter Charts In Power BI

Maps In Power BI

The Key Influencer Visual In Power BI



About Ben Richardson

Ben is a director of Acuity Training which he has been running for over 10 years.

He is a Natural Sciences graduate from the University of Cambridge and a qualified accountant with the ICAEW.

He previously worked as a venture capitalist and banker and so had extensive experience with Excel from building financial models before moving to learn SQL, Microsoft Power BI and other technologies more recently.