A matrix chart in Power BI Desktop is like a table that arranges data in rows and columns, showing a summarized view. It helps compare information, group data, and reveal patterns easily. By organizing data into rows and columns, makes it easier to see how things are connected, helping you understand and analyze information without it being too complicated. This chart allows for drilling down into details for a deeper insight into your data.
How to proceed?
Step 1
Launch power BI desktop app and open the new report page and import the data required.
Step 2
Step 3
Drag the data fields into “Field Section” that you want to analyze using Matrix chart.
Rows: In a matrix chart, rows act like horizontal categories, sorting and displaying different types of information. Each row represents a specific group or item, allowing for easy comparison and analysis across various categories.
Also, you can add subcategories or further breakdowns under each row. This feature allows for a more detailed analysis by expanding the information within each row, helping to explore and comprehend data relationships within specific categories.
Here, I dragged’ Region’ and ‘Medal’. Each country's medal count—gold, silver, and bronze—is displayed under its respective region, showing how many medals each country has won in different categories.
Columns: Columns are used to categorize and display data vertically. They typically represent different attributes, time periods, or additional breakdowns of information. Each column represents specific data or values, allowing for comparisons and analysis across various attributes, providing a comprehensive view of the dataset.
I dragged ‘Year’ field into columns to compare the medals won by countries across different years. This arrangement helps to see how each country's medal count changes over various years.
Values: The "Values" displays the data based on the intersection of rows and columns.
Here, I dragged ‘Medal Count’ in value field. It shows the count of medals for each region categorized by gold, silver, bronze.
Step 4
Filters in a matrix chart enable users to narrow down or refine the displayed data by specific criteria.
Row-wise, I used filters to display only the top 10 regions based on their total medal counts. This setting helps focus on the regions that have the highest number of medals, making the information more manageable and highlighting the most significant data.
Column-wise, I filtered the "Year" column between 2000 and 2016 to compare medal counts across regions during this period. This helps in focusing the analysis on specific years and observing how the medal counts for different regions change over that time span.
Step 5
Customize the appearance.
The "Row headers" option in the format pane of the matrix visual permits adjusting the text attributes in
rows, including size, alignment, background color, and more.
rows, including size, alignment, background color, and more.
Additionally, within the format pane, you have the capability to customize the color and size of the expand (+) and collapse (-) icons, which are used to reveal or hide subcategories in the matrix chart.
"Stepped layout" organizes data hierarchically, displaying it in a structured, multi-level format. The "stepped layout" option can be toggled on or off based on your preference or requirements. Users have the ability to set the indentation level within the stepped layout, adjusting the visual presentation of the data hierarchy.
In the format options of a matrix visual, you can find settings for column subtotals and row subtotals. These settings enable the inclusion or exclusion of subtotals for columns and rows, allowing you to control the display of aggregated values at those levels in the matrix.
Column grand total and row grand total options enable users the ability to format the displayed values according to their preferences or requirements.
Specific column offers the capability to customize and format individual columns based on specific preferences or criteria.
Cell elements-You have the ability to customize the background color of values within the matrix chart based on specific conditions such as maximum or minimum values. Additionally, you can modify font colors, apply data bars, and more, offering various ways to visually represent the data.
In this case, I selected distinct background colors to distinguish between the minimum and maximum values of medal counts. This visual distinction can make it easier to spot the most and least significant values in the data.
Save the visual
Finally, your Matrix is ready. Click save button to save the visual.
When to use Matrix visual?
You can use Matrix visual for following scenarios.
- When you need to compare data across multiple categories or attributes.
- Use the matrix visual for in-depth analysis by expanding or collapsing rows and columns to focus on specific data segments.
- Perfect for hierarchically organizing data, grouping by region, time, or various dataset levels.
Pros
- It supports multi-level grouping, the matrix visual provides a comprehensive view of the dataset, which can be advantageous when handling smaller sets of data.
- Quickly summarizes and adds up values across rows and columns for easier understanding.
Cons
- Too much information shown in the matrix can confuse users and make it hard for them to concentrate on particular details.
- When compared to more visually appealing charts, the matrix visual might seem less engaging or attractive due to its less graphical nature.
Conclusion
Matrix visual is a useful tool for understanding data with its organized structure and ability to dig deep into information. While great for smaller datasets, it can get a bit overwhelming with larger ones. Knowing what the matrix chart is good at and where it might have some difficulties can help users use it effectively to understand data better and make informed decisions.
| Tags | Power BI |
| Useful links | |
| MS Learn Modules | |
Test Your Knowledge |
Quiz |
No comments:
Post a Comment