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Dimension Tables

Overview​

Dimensions are a common concept in data analytics. By dimensions, we usually mean a set of properties that a user, product, or session may have. Examples of user properties:

  • Country of origin
  • Email addresses
  • Primary email address
  • Phone number
  • Is paying
  • First event time
  • Last event time
  • Sign-up time
  • etc.

In addition to user profiles, you can configure a dimension table for any entity you've added on the Entities page.

Most companies store these properties in their data warehouse in separate tables, where each row holds information about a single entity. Later, during analysis, they join these tables to the event tables for further filtering and segmentation.

Mitzu supports joining one or more dimension tables to event tables.

Add new dimension table(s)​

Click the Add dimension table button.

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The modal loads the available schemas from the configured data warehouse connection. Once loading finishes, select the schema containing the table(s) you want to add. After you pick a schema, Mitzu loads every table name in it. You can then choose one or more tables to add, or pick - ADD ALL <N> TABLES - to select them all (where <N> is the number of tables in the schema).

Once the tables are selected, you can choose the entity and enter the Primary key column.

For the Primary key field, set the column that can be used as a joining key when joining the event tables. For example, if you've selected the User entity, set the column that contains the user ID. Type the column name into the input and select it from the dropdown.

If you're unsure what columns are available, click the Fetch columns button. It loads the available columns for all selected tables and populates the dropdown fields with the most common column names.

warning

Fetching columns can take a long time if too many tables are selected.

Click the Add tables button to close the modal and add the new tables configured with the selected entity and primary key.

Configure dimension tables​

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You can update the Entity and the Primary key column in the table. Optionally, you can set Ignored fields to list the columns you don't want indexed.

The Display name prefix (optional) field adds a fixed label to the start of the display name of dimension properties that are newly indexed from this table. For example, with a prefix of User , a freshly indexed country_code property appears as User Country Code. Existing and manually renamed properties are left unchanged, and the prefix is limited to 20 characters. Leave it empty to keep the default display names.

Changes are saved automatically.

warning

Newly added and reconfigured event tables are not indexed automatically. You need to select them and click the Index selected button to index them.

Custom join condition​

By default, Mitzu joins a dimension table to an event table on the dimension table's Primary key column. For most dimension tables this is what you want.

Some dimension tables, however, hold a separate row per entity per date (for example a daily_user_state table with user_id + date). Joining only on user_id duplicates the events. To handle these cases, the Configure dimension table modal exposes an optional Custom join condition text area:

  • Reference event-table columns as __evt_<column> and dimension-table columns as __dim_<column>.
  • Standard comparison and arithmetic operators are supported, as are SQL functions such as date(...).
  • Both sides of the join must appear: at least one __evt_* and one __dim_* placeholder.
  • The expression is parsed and validated before saving — invalid syntax or unknown placeholders surface an error in the modal.

The most common use is matching event timestamps against a dimension date column:

date(__evt_event_time) = __dim_date

Both = and == are accepted for equality — Mitzu normalizes them to the same operator internally.

Leave the field empty to keep the default primary-key join.

tip

Custom join conditions are an advanced setting. Only use them when the dimension table contains time-varying rows that would otherwise duplicate events.

Removing user profile tables​

If you decide to remove a dimension table, select it with the checkbox in the table and click the Remove tables button. This removes the table from the list of tables and from the user property catalog. All saved insights that use one of the removed tables will break.