Data cubes

A data cube is the basic unit of representation of data used for visualization within Imply.

In the data cube you can freely explore the various dimensions and measures in your data.

Shown below is a heatmap visualization from a data cube for Wikipedia edits data, using filters for Latest Day and Language not English, with the Language and Time by Hour dimensions being shown. We'll discuss filters and dimension splits in more detail here.

Cube view heatmap


Filters let you focus on a specific part of your data. It could be a period or time, a certain country or a number of countries, or any other segment of a dimension in your data.

The filters live in the filter bar.

Cube view filter tile

To add a filter, drag a dimension from the dimension panel to the filter bar, or click a dimension and select Filter.

Cube view dimension preview menu

Alternatively click on the + button in the filter bar.

Cube view filter add

You can also add filter by clicking (in some cases also dragging) a segment on the main visualization and pressing Select.

Cube view bar chart highlight menu

There are specific filter controls that are tailored specifically to the type of data being filtered.

Time filters

You can filter on time and select a filter that is relative to the most recent time of the data.

Cube view filter time-type-relative

You can also select a specific time range.

Cube view filter time-type-fixed

Or select a multitude of disjoint time ranges.

Cube view filter time-type-multi

String filters

You can select one or more strings to filter on. These can be selected with the aid of a search.

Cube view filter string

There are other possible filter types that can be used to filter on string data.

Cube view filter string options

You can exclude certain dimensions or select only the values that contain a certain text (or match a regular expression).

Number filters

You can filter on a number range.

Cube view filter number

Dimension splits

Use dimension splits to visually compare several segments in your data. For example, compare different hours of the day to one another, or different countries to one another. The dimension splits live in the show bar.

Cube view split tile

To add a dimension split, drag a dimension from the dimension panel to the "Show" bar, or click a dimension and select "Show". To replace all the existing dimension splits, drag a dimension to the visualization panel.

You can also add a dimension split by clicking the + button in the show bar.

Cube view aplit add

The splits you select will affect the shown visualization.

Cube view split string

Exploring data cubes

Data cubes are designed to be explored quickly.

Find root causes

Contextual exploration

The exploration if focused on contextual cues that allow you to drill deep into your data.

Contextual navigation

Real-time data

Data cubes are dynamic and often backed by streaming data that has frequent, high-frequency updates.

You can adjust how often Imply polls for data updates from the data toggles menu on the header bar as shown below.

cube view real time


All time based calculations performed within Imply are timezone-aware.

You can select your desired timezone from the data cube toggles dropdown menu in the header bar.

cube view timezones




Manage Data

Query Data



Special UI Features