Hierarchy

Hierarchies in data analytics refer to structured levels of data that allow users to view information at various levels of detail. This analytical hierarchy process is particularly useful for drilling into data, providing insights at different granularity levels.

For example, a sales data hierarchy might start with total sales at the top level and then break down into sales by region, country, state, and city. The hierarchy visualization allows users to start with high-level summary data and drill down into more detailed data, enabling deeper analysis and understanding of underlying patterns and trends.

To create a data analytics hierarchy, adhere to the instructions below:

Step 1: After accessing the Hierarchy section. Select the option to add a new hierarchy by clicking the ‘+ Add hierarchy‘ icon.

Step 2: Provide a “Hierarchy name” in the designated field and reorder the categories by dragging and dropping them from higher to lower columns.

Step 3: Save and publish your configured hierarchy.

The Hierarchy screen also provides additional features:

• Hierarchy Name: Displays the designated name for the created Hierarchy.
• Hierarchy Type: Indicates the type of Hierarchy – Local (relevant to your data) or Global (relevant across your organization).
• Action: Offers various options for an existing hierarchy:
  • Click the “eye” icon to view the hierarchy.
  • Click the “pencil” icon to edit the hierarchy.
  • Click the “trashcan” icon to delete the hierarchy.