Advanced Metric Settings

Once you’ve conquered the basics and begun creating new datacards, adding metrics and configuring them, you can explore the advanced metric settings for your datablocks.

To access the advanced metric settings, go into the layout designer (where you go to edit an existing or create a new datacard) and click on the gear icon on the right-hand side menu (next to the layer title or the row name you see when you edit a table).

This will open a new window, where you can modify the core settings of a specific datablock or metric, such as granularity, aggregation and format.

Advanced Popup


On top, the Tabs allow you to navigate from one datablock dimension to another. For example, there are three dimensions included in the line chart: the current trend, the previous trend and the big number at the top. Each dimension can be configured separately, and you can rename the dimension just by clicking on it.

When you have several intervals for a table, these will also show up as tabs. This will allow you to customize additional properties like format settings for a specific interval – for example, you may want to see the monthly value as 1.2M instead of 1,231,543.

Advanced Popup - Tabs

For each tab, you have the option to configure settings ranging from data source to comparison.

Data Source

Data source allows you to select the integration and specify the metric. With some metrics, you can also select a specific attribute you would like to show. For example, selecting Sessions by Channels from Google Analytics will create a dynamic listing of all the channels with their respective values. (Dynamic listings are great for tables and pie charts.) Selecting a specific attribute like Paid Search will only show the sessions value for that specific channel.

Metric Item Tree

Interval and Granularity

Combined, interval and granularity define the range and chunk size of the shown data. Let’s take a look at a practical example. The timeline shown below represents values sent to Databox. You can see different intervals marked with different-colored borders.


Here’s an example for the last 7-day interval. In the image below, which splits this interval by granularity, we can see that daily granularity divides the interval into 7 chunks, while weekly granularity only features a single chunk.


Aggregation Functions

Aggregation functions define the parameters of what we can do with the different data points inside one granularity chunk. It’s used to calculate one “Daily” value (or whichever granularity we’ve selected) from all the data items sent in this chunk (one day).

Just take a look at the previous example, and you can see the actual values for each granularity chunk below the data timeline.

After the first aggregation is applied, we still have multiple values (one for each granularity chunk), which is just enough information for a line graph. But if we want the output to be a single value (like on a “Number” datablock), we need to specify a second aggregation function that will aggregate all the granularity chunk values into one, as shown on the pink line in the example below.


Format and Scale

Scale, in the same way as Format, is used exclusively for the visual representation of numbers. With the default scale and format (“Auto”) option, the number “123456” will be displayed as 123,456. You also have the option of setting it to “Thousand,” which will display the number as 123k.

Metric Comparison

Aside from the obvious choices, you can also compare this metric with another metric, even from a different source. This is usually the “change” shown next to the metric (when set for one-number items) or when tool-tipping (when set on graph items).


If you play around with the advanced settings in this pop-up, you can see the results in the “Data preview” section below.

This article was last updated on April 6, 2016