Power BI is a powerful tool for creating and sharing interactive data visualizations, however, many users are unaware that they can also use Power BI to leverage the power of artificial intelligence (AI) and to gain deeper insights from your data?
In this blog post, I will show you how to use some of the AI visuals in Power BI, such as the key influencers, decomposition tree, Q&A visuals and smart narrative visual. These visuals can help you discover hidden patterns, identify key factors, and ask natural language questions to your data.
Power BI Key Influencers Visual
The key influencers visual lets you analyse how different factors influence a metric or outcome that you care about. For example, if you want to understand what affects customer satisfaction, you can use the key influencers visual to see which factors have the most positive or negative impact on it.
To use the key influencers visual, you need to select a measure (such as customer satisfaction) as the analyse field, and one or more fields (such as product category, region, or age group) as the explain by fields. The visual will then show you a list of influencers ranked by their influence score, and a chart that shows how the measure changes with different values of the influencer.
You can also use the key influencers visual to perform additional analysis such as finding outliers or performing what-if analysis. To do this, you need to enable the advanced analytics option in the visual settings and select a scenario (such as find outliers or analyse what if) from the drop-down menu. The visual will then show you additional insights based on the selected scenario.
Power BI Decomposition Tree Visual
The decomposition tree visual lets you break down a measure by different dimensions or categories to understand its components. For example, if you want to understand how your sales are distributed by different product categories, regions, or channels, you can use the decomposition tree visual to drill down into these dimensions and see their contribution to the total sales.
To use the decomposition tree visual, you need to select a measure (such as sales) as the analyse field, and one or more fields (such as product category, region, or channel) as the fields to expand by. The visual will then show you a tree-like structure that starts with the total value of the measure and expands into different branches based on the selected fields.
You can also use the decomposition tree visual to leverage AI-based analysis, such as finding high or low values or performing root cause analysis. To do this, you need to enable the AI split option in the visual settings and select a criterion (such as high value or low value) from the drop-down menu. The visual will then automatically split the measure by the most relevant field based on the selected criterion.
Power BI Q&A Visual
Sometimes, the easiest way to get answers from your data is to use natural language questions. The Q&A visual lets you ask natural language questions to your data and get instant answers in the form of charts or tables. For example, if you want to know how your sales compare to last year by month, you can simply type “sales vs last year by month” in the Q&A visual and get a line chart that shows the comparison.
To get most value from the Q&A visual, you need to have a data model that is well-structured and has meaningful names for tables and columns. You can also improve the Q&A experience by adding synonyms, phrasings, or featured questions to your data model using the Q&A setup tool in Power BI Desktop or Service.
The Q&A visual supports a variety of natural language expressions, such as filters, aggregations, calculations, comparisons, or time intelligence. You can also refine your questions or explore different perspectives using the suggestions or follow-up questions that appear below the Q&A visual.
The Power BI Smart Narrative visual
Power BI is a powerful tool for creating interactive and insightful dashboards and reports. However, sometimes it can be challenging to communicate the key insights and messages from the data to the audience. That’s where the Smart narrative visual comes in handy.
The Smart narrative visual is visual in Power BI that allows you to add dynamic text summaries to your reports. The Smart narrative visual automatically generates natural language narratives based on the data in your report, and lets you customise them to suit your needs. You can also add parameters, conditional formatting, and expressions to make your narratives more interactive and responsive.
The Smart narrative visual can help you add value to your Power BI reports in several ways. For example, you can use it to:
– Highlight the main trends, patterns, and outliers in your data
– Compare and contrast different scenarios or segments in your data
– Tell a compelling story with your data and guide the audience through your analysis
The Smart narrative visual is a great way to enhance your Power BI reports with dynamic and engaging text summaries. By using the Smart narrative visual, you can make your reports more informative, persuasive, and user-friendly.
Conclusion
AI visuals in Power BI are a terrific way to enhance your data analysis and visualization capabilities. They can help you uncover hidden insights, identify key drivers, and ask natural language questions to your data. You can also customise and fine-tune these visuals using various options and settings to suit your needs and preferences.
If you want to learn more about AI visuals in Power BI, you can check out these resources:
Key influencers visualizations tutorial – Power BI | Microsoft Learn
Decomposition tree – Power BI | Microsoft Learn
Create a Q&A visual in a report – Power BI | Microsoft Learn
Create smart narrative summaries – Power BI | Microsoft Learn
If you would like to learn how to use your Power BI AI visual with your own data, our team provides bespoke Power BI training which can focus on leveraging Power BI AI visuals.
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