This blog focuses on using Power BI comparison charts while creating a report.
We all think that creating a report or dashboard in Power BI is quite easy. With a couple of clicks and a few mouse gestures, voila, our report is ready using Power BI comparison charts! I always wonder, what if my visualization is attractive but without any substance? Does this question also arise in your minds before sharing your reports with the end-user/clients? Have you ever given this a thought that our reports need to be equally “useful” as “pretty” as we build them? After all, we can’t share a report/dashboard with our client which is all sizzle and no steak. Our main motive should be that our end-users can comprehend what the report is about and what each visual illustrates — at a glance!
If we try to visualize our data without a defined aim in mind, we will never be able to produce anything useful. It will be all GIGO, right! Let me draw a picture for you. Suppose we have a client which runs superstores around the globe and we mainly deal with their data which includes- their sales numbers, profit, consumer details like name, region, country, market, type of products, quantity, date of purchase, shipment records, etc.
With the above client data, we can do the following to create an interactive and informative report for them-
- Compare items or show differences over time. For example, Sales made in each Segment.
- Show a relationship between two or more data variables. For example, Profit and shipping cost, by country.
- Find how variables are distributed or how often they occur. For example, Sales made in different regions by year.
In this blog, we will focus only on how to use Power BI comparison charts while creating a report. The following pointers will be further covered for our better understanding-
- What are Power BI comparison charts and how can we use them?
- Overview of different types of Comparison Charts
What are Comparison Charts and how can we use them?
By way of illustration, let’s say we want to display a measure, say sales, for example, and compare it by any classification, let’s assume product category, a comparison (bar) chart will do its magic.
For your better understanding allow me to explain comparison charts briefly-
- As the name implies, comparison charts can be used to evaluate and collate values between two or more data points.
- The prime benefit of using these charts is that we can easily find the lowest and highest values.
When you are figuring out the type of data we wish to communicate and further select the best-suited chart to depict that data, there must be a few questions that might be coming to your mind:
- In a single chart, how many variables do we wish to display? How many are there, one, two, or three?
- For each variable, how many items (data points) will we show? Is it less or more in number?
- Will we show values throughout time, or among objects or groupings of items?
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Let’s begin to match these insights with the following diagram to help us choose the right type of visual-
Once we have enlisted our meaningful insights, we can see that comparison charts are used to achieve one of the following goals:
- Compare two or more values side-by-side to see the difference visually. (example- sales by country- bar chart)
- List important values to find and read them (example- profit per year-line chart)
- Rank multiple data categories from highest to lowest and vice versa (example – sales by product type- column chart)
- Visually showing gaps, spikes, outliers, or trends to demonstrate pattern recognition (example- profit/loss per category and sub-category – table chart)
From the above diagram, for instance, we can conclude that bar charts are good for comparisons among categories, while line charts work better to compare trends over time. Furthermore, let’s dig in and try to understand the most commonly used comparison chart types, their examples, and the dos and don’ts for each chart type.
Overview of different types of Comparison Charts
Using our client’s (i.e., Global Superstore) data, let’s begin discovering the different clustered charts.
1) Column and Bar Charts-
Now, let’s say that you want to build a report where you want a visual to compare Sales value over time, and compare this Sales value for the different regions across the globe where the superstore functions, column, and bar charts, respectively, are the ideal charts for displaying comparisons.
Now you might be wondering why these charts are optimal for such data analysis. From the above charts, we can infer that-
- As a viewer, we are particularly adept at comparing the lengths of bars to find the different values, as the length of the bar is proportional to the value it represents.
- From all the examples we have seen so far, did it occur to you that bar charts and column charts can be used interchangeably? But one key difference which differentiates both these charts is that-
– If you need to compare the change in some parameters over a period, a column chart with time shown from left to right is preferable.
– The horizontal bar chart is a preferable choice if you have many categories or long labels for each data point. It provides more space for each label and avoids difficult-to-read vertical or angled writing.
- Note the order of the bars here. The dataset does not have a unique order, so sorting the bars from maximum to minimum will add a dimension to your information.
- Use a column chart when you want to show trends only when the number of data points is relatively small and when each data point has a distinguishable value.
- When the number of categories is larger than 7 (but not more than 15), or when displaying a set containing negative numbers, you should use bar charts instead of column charts.
- All that rainbow is not pretty. One suggestion I would like to give is that trying using a single color or different shades of the same color is a much better way. You can highlight the bar if it’s the message you want to convey.
Now next in line is the line chart.
2) Line Charts-
Now in my report, I want to visualize data where I want to analyze profit made in each month of a particular year or find out the shipping costs across the various captured markets of our superstore by their shipping mode, line charts will come for my rescue since they are the best to show trends over time or categories.
Now answer a quick question. Which charts do you think are the most effective chart for displaying time-series data? The answer is the Line Charts.
Let me explain to you a few points to support the answer-
- In the first visual of line charts, we can see a trend-based visualization of data over a period. This is where the line charts are a classic.
- You might be wondering if we could have used the column chart as well to depict this example. But the line chart is ideal as it emphasizes the continuation of the flow of data values.
- From the second visual we can conclude that line charts can handle multiple data points and data series. This further assists in easier readability.
- One more point that you should note is the dots should be arranged in a manner that the time flows from left to right while using a consistent time interval.
3) Scatter/Bubble Charts-
Next in my report, I want to analyze the correlation between sales and quantity across different regions. This bubble/scatter chart can come in handy.
But what is the difference between the two? This question might be coming up in your mind. So, allow me to simplify it for you.
- Scatter plots generally compare two values. But if you add bubble size as the third variable, bingo, you get a bubble chart that helps you in comparison of the other two correlated values.
- So, simply we can say that a scatter chart displays the relationship between the two numerical values, and a bubble chart helps to show the data set with three dimensions.
Your Power BI report is useless without the correct graphics. To showcase powerful insights, you’ll need to know when and how to use various visualizations, so you don’t waste time creating reports that don’t have an impact. There are many charts available for visualization. Choosing the accurate visualization is paramount when you are publishing/sharing your report with clients/executives. One such way to visualize data is to compare one data value with others using comparison charts. These Power BI comparison charts help understand complicated data, find patterns, identify trends, and tell a story.
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