Adding metrics and attributes


After you create a connection, your data is broken into metrics and attributes. Metrics are all quantifiable values such as sales, costs, profit, unit price, quantities, etc. Attributes are non-quantifiable values like date, locations, and product ID. 

Tip: Learn more about how to perform SQL queries without SQL in Andrew Forbes' tip, Performing analyses without SQL.
This article covers the following:

Adding metrics

Metrics are added to the Metrics portion of the frame. You can add a normal metric by clicking the button, or you can add metrics in different sizes, colors, on a dual axis, to a trend line, or include them in datatips.

BIME will automatically take the sum of the metric's data. You can change how your metric is calculated by clicking on the metric, then selecting a new aggregator. For more information, see Metric aggregators.

The following are the custom metric options available:

Note: A metric can only be one of these custom options at a time, except if datatips are added in the Chart configuration menu.

Color and size

You can show the differences in a metric's results with color or size encoding. To add a color encoded metric, select the color encoding icon () at the bottom of Metrics. To add a size encoded metric, select the size encoding icon ().

At the upper right of your chart, you can view the colors or sizes representing the highest and lowest results. You can change the color style in Chart configuration > Colors, then select a new style from the Color encoding drop-down list. Size options cannot be edited.
Note: You must have another metric on the frame before adding a color or size encoded metric.

Below are examples of the metric Replies as color and size encoded.

Color encoded:

Size encoded:

size encoded report

Dual axis

On some charts, you have the option to add a metric on a dual axis. This is an easy way to compare metrics with different scales.

For example, in the image below, # Incidents uses a much smaller scale than # Replies and # Tickets. If # Incidents was not on a dual axis, it would only appear between the 0-350 range, so the results would be difficult to view.

# Incidents as a normal metric:

Quantity as a normal measure, difficult to see

# Incidents on a dual axis:

Quantity as a dual axis measure, easier to see

As you can see, it is much easier to compare results when # Incidents is added on a dual axis.

To add a dual axis metric, select the dual axis icon (). You can edit the dual axis in Chart configuration > Dual axis.

Trend line

Similar to a dual axis, you can add a metric as a trend line to display a metrics results as a line. Select the trend line icon () to add a metric as a trend line.If you would like separate lines displaying the trend for each metric result, you will need to add a trend line in Chart configuration>Trend line


Note: If one of your metrics is added as a trend line and you add a trend line in Chart configuration, an additional line will not appear for that metric. 

Trend line report

You can edit trend line options, including hiding and displaying values in Chart configuration>Trend line


You can choose to have a metric be only available as a datatip by click the tooltip icon(). If you add your metric as a datatip, it will disappear from your report and you will need to manually add the metric to your datatips in Chart configuration>Datatips. For more information on adding adding and customizing datatips, see Adding datatips to your query.



Comparison lines

Comparison lines can highlight multiple metrics' results for one value. When you add a comparison line, you can hover over any data point to view all results for the same X axis location. Comparison lines are useful when your attribute has several values, but your screen size each label. For more information on comparison lines, see Adding datatips to your query.

To add comparison lines:
  1. Open the Chart configuration menu, then select Datatips.
  2. Select Comparison lines from the Mode drop-down list.

Adding attributes

Attributes slice your data by non-quantifiable values. They can also be used to select or exclude results from your chart. You can choose values to display by clicking on the attribute after it is added.
Note: Excluding might be more appropriate than selecting for datasets that change over time, such as Google Analytics.
Attributes can be added to the following places:


Columns will slice your results by the attribute's values. Attributes added to Columns will appear on your report. You can add an attribute to Columns by clicking the button and selecting an attribute from a folder or using the search

Below is an example with the attributes Year(Date) and Month(Date) added to Columns. For Year, the value 2014 is selected, so only results from 2014 will be displayed.

Columns graph


If you add an attribute to Rows, you can see individual charts for each of your attribute's values without selecting or excluding results. You can view a value using the Row Selector to the left your chart. The Row Selector lists all values of the attribute and can be edited in Chart configuration > Row selector.

Below is an example of a report with Country added to Rows. The value France is selected in the Row Selector.

Row selector


Attributes added to Filters will not affect your report, unless you choose to select or exclude values. Your results will then be filtered to your selected values, but the attribute names will not appear on your chart. Instead, all you applied filters are listed underneath your report. This list includes any result manipulations you create.

Filters are useful for when you want to choose values from several different attributes, but do not want all attributes shown on your chart. For example, the results below are filtered by the category 'Accessories' and the country 'France', but the attribute names are not shown on the graph.


Similar to Rows, attributes added to Explosions will break your report into individual charts based on the attribute's values. Unlike Rows, Explosions show all charts side-by-side. This provides a simple way to compare results, but if your attribute has several values, you should consider selecting values to display or using Rows.

Explosions graph

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