Group and Filter by Dimensions

An important part of the metric process is to be able to view the data as well as slice, dice, and group it easily by particular dimensions. The chart on the metric page allows you to do all of these things. The default chart on the metric page will load the last 365 days worth of data.

Changing Date Ranges

When you open the "Edit Chart" menu on the metric page underneath the chart, you will see a Date Range selector. This allows you to change the default time range of data to select the desired time period. The date range selector provides a number of common presets, such as the "Last 7 days" and "Week to Date", as well as a custom time range selector, where you can select a start and end using a calendar.

Filter and Group By

Filtering and grouping by dimensions is one of the most common analyses performed on a metric value and is a key part of Transform. For example, "I want revenue by country!", where country is the dimension and revenue is the metric.

Users can filter and group by dimensions using the metric chart. Dimensions are organized by the data source identifier that the particular dimension comes from. For more information on identifiers, data sources, and dimensions, please refer to the Metrics Framework.

Filter

Under "Filter By" in the "Edit Chart" menu, you are given the option to select a filter. A filter is essentially a dimension in the data. A dimension can be time-based, like "last login date" or categorical, like "country" or "product line".

The menu to select dimensions is searchable and is split up by an identifier hierarchy. You can search either by identifier or by the dimension name. The identifier maps to the primary identifier of the source of data, or table, that the dimension comes from. For example, a dimension called "Organization Name" might have an identifier called "Organization", since it came from the Organization table. The identifier hierarchy is useful to organize dimensions when there could be many, or if there are multiple similarly named dimensions across tables.

Once you find the right identifier, you can see a list of dimensions associated with it, and once you select a dimension, you can see all the values associated with the dimension in the filter value menu, with checkboxes next to each. Select the dimensions that apply in your filtering, and you'll notice the graph view will change and prompt you to "Update Chart" to view the data you are selecting.

Local Dimensions

Dimensions are an entity of the primary key. In some cases, data sources do not have a primary identifier. This means the dimensions defined in these data sources can only be used locally and cannot be use to join across other data sources. Our dimension dropdown menu exposes "Local Dimensions" at the bottom of the menu (you can also search for "Local" to find them).

Group By

You can also group metrics on the chart by a given dimension. Similar to filtering, you'll find this in the "Edit Chart" menu. The grouping functionality will show multiple lines for the given number of potential values present in your data set. For example, if your dimension was "country", and you had 3 countries in your dataset, we would display a unique line for each, and the legend will provide information on which color corresponds to which dimension value.

By default and for metrics based on additive measures (measures that use an aggregation type of sum or sum boolean), we will show top 25 dimensions on the chart. The remaining will be summed and grouped into an "Other" category so we do not crowd the chart. You can optionally select "All" in the dropdown next to the grouping menu to see all dimensions or select a specific number of dimensions to show. Additionally, when you export data as CSV, it will give you a choice to export the entire dataset with all dimension values, or to export the limited version of what's shown on the chart.

When using group by, the tooltip (which you can see by hovering over the chart) will display a total for each day at the top. The total represents the sum of all the groupings and will be present for metrics that are based on additive measures.