I am sure all of us have dealt with the problem of selecting appropriate data visualization for the data sets we have. The right data visualization will boost the impact of storytelling with data and informed decision making.
Enterprise level business intelligence platforms like PowerBI help in dealing with visualizing volumes of datasets in the most convenient manner.
PowerBI is a powerful business intelligence tool developed by Microsoft that helps users create interactive visualization using business intelligence. Best part is users could create appealing reports and actionable dashboards by themselves without taking external help.
As much as PowerBI is simple and user-friendly, it is also packed with a several visualization options. A lot of people seem to have confusions in deciding the right type of chart for their data.
Let’s understand the different types of charts available in PowerBI in order to select the right one.
Area charts are based on line charts where the area between the x-axis and the line is filled with some color, pattern or texture.
Area charts are primarily used:
However, area charts can get overwhelming when dealing with multiple categories.
Google’s musical timeline from the 1950s to 2010 is a good example of area chart.
The below example shows the Number of Units Sold by a Company across different geographic regions over a period of 2 years.
From the above chart, it is quite clearly visible that the number of units sold by a company has been on the rise for the past 2 years.
Bar charts are horizontal charts that represents or compares categorical data. They can also be used to represent negative values.
Bar charts are used
Though bar charts is used to show comparison between data, it cannot be used to study the relationship between those data.
The above chart shows the number of units sold by a company by drawing a comparison between 5 countries (Canada, France, Germany, Mexico and USA). From the above chart, it is evident that Canada has sold the most number of units while Germany has sold the least number of units.
Clustered column charts are quite similar to bar charts, the only difference is that clustered column charts groups the data from the same category into a cluster. The data within clusters can be compared with each other as well as with data from other clusters.
For example, the quarterly sales of each product can be grouped together. Each product will have 4 bars representing each quarter: Q1, Q2, Q3 and Q4. This can help identify which product is generating a lot of revenue and this lets you see how each product’s sales has changed over time.
Combo charts as the name implies is a combination of column chart and line chart. Combo charts are used to combine measure values that are normally hard to combine because they belong to different scales like units sold and revenue.
For example, combo charts can be used when you want to compare the actual sales for a company against the budget allocated to achieve the sales.
Doughnut charts are named as they resemble a Doughnut. They are similar to pie charts and they can be used to show the composition of the whole data in proportions. Doughnut charts prove to be most useful when required to exhibit the various proportions that make up the final value.
For example, Doughnut charts can be used to show the percentage of revenue generated per quarter of the financial year.
In the above chart, you can see the price of manufacturing categorized by product.
Funnel charts are used to show the process that leads to a conversion. They are a good option when the data is sequential and when the first stage has a larger number of “items” than the final stage. It is similar to a marketing funnel which shows stages or steps that transforms a non-customer into a customer.
Gauge charts are used to show the progress towards a particular goal i.e. it helps in showing how much of a particular goal has been completed. Gauge charts are used to represent KPIs such as yearly sales goal of a company. The minimum and maximum values are predetermined and the line in the middle determines how far you have progressed towards your goal. Gauge charts are visually appealing but they can also be space-demanding as well. If you feel that less is more, then you can consider KPIs over gauge chart.
Line charts are a graphical representation of a series of data points all connected by a straight line and it is used to represent continuous data sets. Line charts can be used to show the exact value of the plotted data. For example, Line charts can be used to display monthly trends of products sold. Arguments arise with respect to the measurement between time points. Some believe that data may be measured continually while others believe that measuring data at occasional intervals is sufficient. Line charts should only be used for time series or to measure trend over a period of time e.g. dates, months, years etc.
Pie charts are used to show the composition of the whole data in parts. Each component of a pie chart is represented in percentages and the sum of all the parts should equal 100%. Each proportion of a pie chart can be divided into slices. Since the proportions in pie charts are divided into slices, it can be difficult to identify the sizes just by glancing at them. Pie charts come in handy when dealing with categorical data. Make sure you have the necessary data that reflect this type of chart. This chart however can be used with only one set of data. Examples of pie chart can be to analyze the percentage of units sold by geographical region.
Scatter plots can help to display the relationship between two variables for a set of data. In scatter charts, data points are plotted along their axis but unlike line charts, they are not connected by a straight line. Scatter charts can help to determine the correlation whether positive (both variables move in same direction), negative (both variables move in opposite directions) or no correlation (there is no relationship between the variables). For example, Scatter charts can be used when measuring the correlation between employee’s income and their happiness.
Waterfall charts can be used to show how an initial value has been affected by adding or subtracting subsequent values to the initial value to arrive at the final value. For example, waterfall chart can be used to track the revenue for the entire year to determine the net profit at the end of the year. Let’s say you have been tasked to plot your company’s annual profit. You can add the various sources of income and after deducting the cost you will arrive at the profit or loss. In such a scenario, waterfall chart can be useful.