Power BI Matrix & Table both are most frequently usable visuals used for presenting data in tabular format.
- In table we present data in 2-Dimension data grid format.
- By default display all data, means flat data structure.
- Rows not fixed but columns are fixed.
- When you add new dimension you can add them as “Values” and it will appear as a new column in grid.
- It support Multidimensional data grid format.
- Matrix automatically aggregate the data according to data behavior.
- Rows & Columns both are not fixed.
- Here you have option to add Values, Rows & columns.
Important Note : Show values on rows for matrix visual
Here are some additional differences between a matrix and a table visual in Power BI:
- Hierarchical grouping: A matrix visual allows you to group and summarize data by multiple hierarchical levels, which can be helpful when analyzing data with multiple dimensions. In contrast, a table visual only displays data in a flat, one-dimensional view.
- Dynamic columns and rows: With a matrix visual, you can dynamically add or remove columns and rows based on the data or user input, which can help you explore and analyze data more flexibly. A table visual, however, only shows the columns and rows that are explicitly defined in the data model.
- Subtotals and grand totals: A matrix visual can display subtotals and grand totals for each row and column, which can provide a quick overview of the aggregated data. A table visual, however, does not offer this functionality by default.
- Drill-down capability: A matrix visual allows users to drill down into specific data points to explore more detailed information, while a table visual only displays the data as-is.
Let’s start with an example:
Download Sample data : SuperStoreUS-2015.xlxs
Now, create a table visual using three fields: Customer Name, Customer Segment, and Discount.
In this dataset, there are multiple entries for the same users against different Customer Segments and Discount values.
By default, the table visual will display all the data in a flat data structure.
And when we display same data in Matrix Visualization, it will aggregate the data automatically, so you can see the output in below screen shot now Customer name is not repeating.
For Data Analysis purpose, the Matrix Visual is good and easy to understand. In the Matrix, we can transform the data column-wise, which provides a comprehensive view of the data.
Refer to the screenshot below, where we are displaying the data column-wise using the Matrix’s three properties: Rows, Columns, and Values.
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