Slicers versus columns and rows

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1. Overview

This article describes the purpose of slicers, columns, rows, and measures in the Data Analysis Panel.

The Data Analysis Panel appears when you drag and drop data onto a metric set, or the canvas of a dashboard or other view. If closed, you can re-open it from the toolbar or context menu for a data visualization.

2. Data Analysis Panel

The Data Analysis Panel lets you build a view of your data simply by dragging data from the Explore window.

Type	Purpose	Visible
Measures	Display numeric/fact values	Yes
Rows	Group by values into rows/data points	Yes
Slicers	Filtering only	Limited
Columns	Group by values into columns/series	Yes

The figure below shows the Data Analysis Panel for a table visualization.

Tip

If you're not sure where in the Data Analysis Panel to drag data, just drop it onto the visualization instead.

3. Measures

Add data under Measures in the Data Analysis Panel to display the numeric values you are interested in viewing (such as sales or stock levels). Measure values will be grouped into the Rows and Columns data that have been added, and filtered by Slicers, if any.

In a table visualization, each measure appears as a column. When selecting measures together with data under Columns, the measure columns will reoccur for each column hierarchy value (as seen under Accessories and Bikes below).

Measures displayed for each product category in a table

In a chart, each measure is displayed as a series of data points, each with a different color by default.

Two measures displayed as a bar chart (without grouping into additional columns/series)

Tip

To display a row or data point for each measure instead of a column or series, you can transpose the metric set.

4. Rows

Data can be added under Rows in the Data Analysis Panel to group the measures by these values into rows, such as sales broken down by year instead of just a single total sales value.

This data often consists of text or date/time values, and is called a hierarchy (or dimension) in Dundas BI.

Row hierarchy members in a table visualization

If you add multiple hierarchies, a row will be displayed for each combination of their values in the data, for example for each year and for each country.

In a bar chart, rows of data are displayed as data points (bars). These will often be displayed along a chart axis to correspond with each data point.

5. Slicers

Data can be added under Slicers in the Data Analysis Panel when you only want to filter by those values. In our example shown below, all the data displayed in the table is filtered to only online orders by filtering a column of true/false values named OnlineOrderFlag to the value True.

The slicer values selected for filtering can be displayed in tooltips and labels, which will be the same for the entire visualization. If you want to display different values in each row, column, or data point, you can add this data elsewhere on the metric set instead of Slicers.

After adding data under Slicers, click its filter icon and choose the values to filter by.

In a dashboard or another view, you can also add a filter to your view connected to this slicer, or connected to any other hierarchy or measure.

6. Columns

Data can be added under Columns in the Data Analysis Panel to group the measures by the selected values into columns.

This is similar to Rows, but since measures are normally each displayed as a column, measures will be repeated for each column hierarchy value.

Column hierarchy members appear as another row of column headers in a table visualization.

Column hierarchy members in a table visualization

In a bar chart, each column hierarchy member splits each series of bars into separate series, where each series is colored differently by default.

Column hierarchy members in a bar chart. There were originally two series, and each has been split into three: one for each hierarchy member

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