1. Visualization options
Hi there! Great job on completing the first two chapters. I'm Sara, and I will be your instructor for this chapter, where we'll focus more on visualizing data with Power BI.
2. Visualization types
Power BI provides a number of different visualization types that you can use in reports. So far we have only looked at a few of them. Let's find out what else is possible in Power BI!
In this course, we'll only focus on what type of visualizations you can make with Power BI. Obviously, it's also extremely important to know when to use which type. You can learn all about this in DataCamp's Understanding Data Visualization course.
3. Column and bar charts
Bar and column charts help you look at a specific value across different categories.
So what is the difference between the two? The answer lies in the representation. If the rectangles are placed horizontally then the visualization is a bar chart. If the rectangles are placed vertically then the visualization is a column chart.
4. Column and bar charts
There are a number of different column and bar chart types available in Power BI.
A stacked bar or column chart includes multiple elements in one bar. It shows the different series as a part of the same single column bar, where the entire bar is the total.
A clustered bar or column chart shows multiple bars to represent values, but this time they are located next each other instead of being stacked.
A 100% stacked bar or column chart shows the relative percentage of multiple data series in stacked bars, where the total of each stacked bar always equals 100%.
A combo chart combines a column chart and a line chart.
5. Line charts
Line charts show multiple lines in one chart. They emphasize the overall shape of an entire series of values, usually over time.
6. Area charts
Area charts are based on line charts with the area between the axis and line filled in.
7. Pie and donut charts
Pie charts show the relationship of parts to a whole.
Donut charts are similar to pie charts. They show the relationship of parts to a whole.
8. Tree maps
Tree maps are yet another way of showing the relationship of parts to a whole. They are charts of colored rectangles, with size representing the proportional values.
9. Some other visualization types
The next set of visuals are designed to show one or two values and are used for showing the overall level of performance.
Cards show one value, whereas multi-row cards can display multiple. Gauge and KPIs are designed to show actual data compared to budgeted data.
10. Table and matrix
Both of these visualizations show detailed text data in a tabular format. A table is a grid that contains related data in a logical series of rows and columns. It may also contain headers and a row at the bottom for totals.
A matrix is similar to a table in that it is made up of rows and columns. However, a matrix can be collapsed and expanded by rows and/or columns. In the example, you can see that we expanded the data to focus on region for mobile loads of Page1.
11. Editing visualizations
All the charts we just discussed can be edited using the options included in the paint brush. We'll take a closer look at how to do that in the next video.
12. Contoso data warehouse dataset
This chapter uses data from the Contoso Data warehouse. Contoso is a fictional online retail company that is working on trying to meet sales goals.
13. Contoso data warehouse dataset
This dataset is made up of multiple files. The fact table is called FactStrategyPlan and it contains data on the sales transactions of the company.
The dimension tables hold more information about these transactions. We'll work with the account, date, entity, product category, and scenario dimension tables.
14. Let's practice!
Let's see how well you understand the different visualization types!