Q&A visuals are an incredible feature that allows you to explore your data in a more interactive and intuitive way. By simply asking questions in natural language, you can uncover insights and trends that would have been difficult to find otherwise.
Popular use cases for Q&A visuals in Power BI:
- Exploratory analysis: The Q&A feature can be used for exploratory analysis of data. Users can ask questions such as “What are the top products by sales?” or “How are sales trends by region?” and receive instant answers in the form of interactive visuals. This allows users to quickly and easily explore the data and identify patterns and trends.
- Ad hoc reporting: The Q&A feature can also be used for ad hoc reporting. Users can ask questions such as “How many sales were made by product category in the last quarter?” or “What is the average revenue per customer?” and receive instant answers in the form of interactive visuals. This allows users to quickly generate reports and dashboards without the need for complex queries or programming.
- Data validation: The Q&A feature can be used for data validation. Users can ask questions such as “What is the minimum and maximum value for a particular metric?” or “How many records are in the dataset?” and receive instant answers in the form of interactive visuals. This allows users to quickly verify the accuracy and completeness of the data.
- Collaboration: The Q&A feature can be used for collaboration. Users can ask questions and share the resulting visuals with others in the organization. This allows for a collaborative approach to data analysis and can help facilitate data-driven decision-making.
Learn how to make the most out of Q&A visuals:
- Start with relevant data: Before we begin exploring Q&A visuals, it’s essential to have relevant and high-quality data in your Power BI model. Ensure that your data sources are reliable and the data is clean, accurate, and up-to-date.
- Utilize synonyms: Power BI is quite intelligent when it comes to understanding synonyms. Nonetheless, defining synonyms for your data is a good practice to ensure that users can easily interact with Q&A visuals using various terms. For example, if you have a field named “Revenue,” you can add synonyms such as “Sales,” “Income,” or “Earnings” to make it more accessible.
- Set up featured questions: Create a list of featured questions that users can choose from to get started with the Q&A experience. These questions should cover common inquiries and key insights that your users might be interested in. For example, if your dashboard is about sales performance, you could include questions like:
- What was the revenue last month?
- Which region had the highest sales?
- Who was the top salesperson last quarter?
- Display a suggested list of terms: When users type their questions in the Q&A visual, Power BI provides suggestions based on the available data. To make the experience smoother, you can display a list of common terms and phrases that are relevant to your data, helping users quickly access the information they need. This step can also reveal any issues with the data model that might be hindering the Q&A experience.
- Experiment with natural language: One of the strengths of Q&A visuals is their ability to understand natural language. Encourage your users to ask questions in various ways and use different phrasing. Doing so will help uncover more insights and improve the overall user experience.
- Combine visuals for better insights: While Q&A visuals can answer users’ questions quickly, they might not always be the best way to display the information. Consider combining Q&A visuals with other chart types to create a more comprehensive and engaging dashboard. For example, you can display a Q&A visual for finding the top seller alongside a bar chart displaying the sales breakdown per product category.
- Train and educate users: To get the most out of Q&A visuals and Power BI in general, educating your users about best practices, data interpretation, and report navigation is essential. This will ensure that users feel confident in interacting with the Q&A visual and making data-driven decisions.