Welcome to the final installment of our three-part blog series exploring Power BI’s Powerful Visualizations. In our previous two blog entries, we explored Bar and Column, Line and Area, Waterfall, Funnel, Scatter, Pie, Donut, Treemap, Maps, Gauge, Card, and KPI charts. In this blog post, I will provide an overview of the remaining three chart types: Slicers, Tables and Matrixes, and AI-Enhanced Visualizations.
To start this section, we are going to talk about ‘Slicers’ as a whole. In this group, you’ll find the Vertical List Slicer (emphasized in red in Figure 1), the Dropdown Slicer (highlighted in blue in Figure 1), the Tile Slicer (marked in green in Figure 1), and the Date Slicer (distinguished in purple in Figure 1).
‘Slicers’ are used to filter down data without having to add filters into the visualizations themselves. For instance, if I were to click on ‘Amarilla’ in the Vertical List Slicer, all the visuals would then exclusively display data pertinent to that specific product. The same principle applies to Dropdown and Tile Slicers. If I were to select a specific ‘Discount Band’ from the Dropdown Slicer or a ‘Segment’ from the Tile Slicer, the visuals would automatically adapt to present data relevant to the chosen selection. Lastly, there is the Date Slicer. Lastly, there’s the Date Slicer. With various available formats, I’ve chosen the ‘Date Slider’ format here. This format enables me to select a date range by adjusting the start and end points, causing the visuals to dynamically showcase information solely within that selected date range.
Following the ‘Slicers’ section, let’s now shift our focus to the Tables and Matrix charts. In this group, we have, as you might have guessed it, Tables and Matrixes. I have the Table (highlighted in red in Figure 2) and I have the Matrix (highlighted in blue in Figure 2).
Tables are very useful for displaying all of your data or just specific columns to see how they relate to each other without needing a visual. The Matrix is just Power BI’s version of the Pivot Table. It is really cool because it can take 2-dimensional flat data, like in a table, and give it a 3-dimensional feel by having the stepped layout and aggregating data using the drill-through features.
Now onto the fun part where we will cover all of Power BI’s ‘AI Visuals’. In this group we have the Key Influencers (highlighted in red in Figure 3), the Decomposition Tree (highlighted in blue in Figure 3), the Q&A (highlighted in green in Figure 3) and the Smart Narrative (highlighted in purple in Figure 3).
The Key Influencers Visual is a machine learning solution that is used to analyze data and make decisions faster. It takes all entered data into account in order to rank the factors and display them as the Key Influencers. It also gives top segments of the data you enter for both categorical and numerical metrics. In the Key Influencer Visual the data it returns tells me that when the Sum of Sales is between 27,234.9 and 55,071.2, the average of Units Sold increases by 933.7 and more.
Next, the Decomposition Tree is another powerful AI Visual in Power BI’s suite which is used for ad hoc exploration and finding the root cause of specific metrics performance. It lets you visualize data across multiple dimensions and allows you to drill down into any of the dimensions in any order. It enables you to visualize hierarchical data so that you can accurately find key drivers of metrics or outcomes in your data. In my Decomposition Tree, I start with the ‘Sum of COGS’ and break it down to see how the ‘Sum of COGS’ for each ‘Country’ measures up against the others. The next dimension, the ‘Product’, allows us to see which products in the selected country have the highest COGS.
Following the Decomposition Tree is the Q&A visual. Q&A enables the user to enter in a question or specific criteria into the text bar and then Power BI will create a visual or return text based on what would appropriately represent the data you are searching for to the best of its ability. Q&A is also very powerful because it allows the use of “natural language query” meaning you don’t have to type in code to get what you want. For example, I searched “profit by month and country” and Power BI identified that I was asking for the profit from month to month in each country and created a line chart to display the data accordingly.
Finally, we arrive at the final visual of this blog series, the Smart Narrative. The Smart Narrative is a visualization tool that can provide a quick text summary of any visuals or reports. It uses “natural language” processing in order to decipher what the user is looking for and will automatically generate text based on the visuals or reports in order to explain the data it contains.
I thank you for following along with the blog series and reading through what I had to say on all of these visuals in Power BI. I hope you have a great day! If you haven’t already read parts one and two you can read part one by clicking here and part two by clicking here.
Bailey McDonald
Data Engineer, Patriot Consulting
Email: bkmcdonald@patriotconsultingcorp.com | Blogs: Patriot Consulting Blogs
LinkedIn: Personal: BaileyMcDonald | Company: Patriot Consulting
