Overview

Heap Connect can export your data to S3 or to three dynamic data warehouses: Redshift, BigQuery, and Snowflake. All exports are completely retroactive, just like the Heap dashboard. As you label new events and modify existing events, we seamlessly update your cluster schema with all historical data for synced events, which ensures that Connect always provides a clean and accurate representation of the data received since you’ve been using Heap.

Data Hierarchy

In Heap, all data is hierarchical: you have many users, who conduct many sessions, and every session has many events, as shown in our data model. As a result, you can have metadata attached to every level of this hierarchy, which we refer to as user, session, and event-level properties. Any information on the user level propagates to the session and event level, and any information on the session level propagates to the event level.

For example, any user property (ex. email address) is available as a property on the session and event level in Heap, and any session property (ex. UTM Source) is available as a property on the event level. However, any event-level property (ex. URL Path) is not available on the session or user level, since it pertains to only where the event itself occurred. For a complete list of all of the information we collect out-of-the-box for each type of property, see Autocaptured Data.

Heap Connect adopts a similarly hierarchical schema. By default, every environment schema will have the following tables:

• One users table (for all user information)
• One sessions table (for all session information)
• One pageviews table (for all pageview information)

You can also choose to sync any labeled or custom event in Heap, which will add a new table to the schema for each synced event. For exports to a data warehouse, we’ll also create a table entitled all_events, which includes basic information about every event in the synced event tables joined for ease in aggregate analysis.

It's important to note that Heap Connect contains all of your labeled data in Heap that you've selected to sync downstream. Out-of-the-box, Heap will automatically collect all user interactions (pageviews, clicks, etc.), which we refer to as raw data. Labeling events in Heap allows you to apply an intutive name to raw data. For instance, clicking on a cta.signup might mean that a user signed up, so you might add the label Sign Up.

After a user labels an event and syncs it to Heap Connect, Heap will automatically sync all of the historical data associated with the event in its own table, and include these events in the all_events table. Learn more about labeling events in Events overview.

Schema

All data in your account is hosted within a single cluster or datasets (BigQuery) under that project.

By default, these are named using the project name, then an underscore, followed by the environment name. For instance, each table in your main production environment will be part of the main_production schema, while the tables in the development environment of a project named "My iOS App" will be in a schema or dataset called my_ios_app_development.

For each environment, Heap will create the following tables (known as views in BigQuery):

• One users table
• One sessions table
• One pageviews table
• One table for each event you've labeled and synced in the Heap interface
• One view for each segment you've labeled and synced in Heap (Redshift and Snowflake only)
• One all_events table, which contains the built-in pageview event and all labeled or custom events synced
• One _sync_history table
• One _sync_info table
• One _dropped_tables table 
• One user_migrations table which lists all instances of merging and migrating users
• One _event_metadata table

These tables have a dynamic schema, which auto-updates to reflect any new events or properties you've tracked.

Users Table

This table is called users. It resides under the projectname_environmentname schema. It contains a row for each user in the environment. The column schema is:

Sessions Table

Note that "server-side sessions" will not appear in this table, and only appears in the users view in-app. Data for server-side events toggled to sync can be found in the all_events and event tables. The sessions table has the following schema:

Pageviews Table

Heap will create a table that contains every pageview by default.

Event Tables

Heap will create one table for every labeled event you've created within Heap and synced downstream.

For each event table, the columns are determined by the version of the Heap library that sent the event, along with any custom properties you may have added via snapshots, the custom API, or defined properties. For instance, if an event was sent by the Heap iOS library, its SQL table would contain iOS-specific columns like app_version or carrier, but not web-specific columns like landing_page or referrer. This helps keep your schema as clean as possible.

Note the following about labeled properties in Heap Connect:

• Labeled properties are supported for all Heap Connect destinations.
• The default pageviews and sessions tables include labeled properties (Redshift, Snowflake, S3 only).
• The default users table does include defined properties but, because that table doesn't include the Initial properties you see in Heap, won't contain values for properties relying on those, e.g. Initial Marketing Channel or Initial Browser. For information on adding Initial properties to the users table, see our Heap Connect Common Queries.

The name of these tables will be the event_name itself and remain under the projectname_environmentname schema. To produce the event_name portion, we strip the event name of any non-alphanumeric characters and snake-case the result. For example, an event named "Sign Up - Click Link (Any)" becomes sign_up_click_link_any.(Note that this means it's possible for events to collide into the same table name. Make sure your event names are sufficiently distinct!)

The name of the event table is created during your first sync and it doesn't change after that. Heap will pre-populate the name field for you before your first sync, but you have the option to rename it.

If you change the display name of a synced event in Heap later, it won't change the event table name downstream.

Each of these event tables will be fully retroactive, meaning it will contain a row for every occurrence of the event since the day you installed Heap. The column schema is:

Segments View (Redshift And Snowflake Only)

Heap will create one view for every defined segment you've created within the Heap interface. These tables only contain one column (user_id) that you can use to join against all other user information (users or other event tables).

All Events Table

Heap will create a table called all_events, which contains all labeled or custom API events, pageviews, and sessions you have synced, as well as the built-in pageview event. The all_events table is created on top of the other event tables, and includes an extra column event_view_name that denotes the source table of each row. It will have the following columns:

BigQuery Limitations

In most cases, the schema for the all_events view will consist of the union of all columns from all event tables, with nulls filled in where applicable. However, if you are syncing many tables to your project, this can run into BigQuery query length limits, in which case we'll fall back to one of the following reduced column sets:

1. All built-in Heap columns - i.e., event_view_name and columns contained in the pageviews/sessions tables
2. Basic columns - event_view_name, user_id, event_id, session_id, time

If your all_events view is created with a reduced column set, you can join it with the underlying event views to access any property columns that are not available in the view.

Sync History Table

Heap creates a table called _sync_history that contains a record for every attempted sync. This table is helpful for monitoring sync performance and scheduling dependent jobs. All timestamps are in UTC for Redshift and BigQuery and in local time for Snowflake.

Sync Info Table

Heap creates a table called _sync_info that contains metadata around the sync process and last updated times.

Dropped Tables Table

Heap creates a table called _dropped_tables that contains a record of all data tables and views that were dropped as part of an update.

User Migrations Table

When a user is identified, a migration occurs to aggregate the data under the new identity. These migrations are recorded in this table.

Event Metadata Table

This table contains metadata about the names of events, which allows you to build automated jobs that use this metadata. This table is re-created on each sync to stay updated with the latest event metadata.

Event_metadata shows up differently for S3. You can query the table as follows.

{ui_name: 'Stripe charge',
  table_name: 'stripe_charge',
  source: 'stripe',
  last_updated_at: '1609459200000',
  last_updated_by: 'sales@heap.io',
  notes: 'This is a note',
  verified_at: '1640995200000',
  verified_by: 'heappo@heap.io',
}

Data Syncing

As you labeled and sync new events and modify existing synced events, we seamlessly update your cluster schema. This ensures that the data is always a clean, accurate representation of your raw data.

In particular, the following changes can happen on each sync:

• When an event is toggled to sync for the first time, we create a new table for that event.
• When a synced event label is modified in the Heap interface, we tear down the existing table for that event, create a new one in its place, and populate the new table.
• Archiving events and properties that are synced downstream will pause these syncs indefinitely until they are restored. Specifically:
  • Archived events will stop syncing downstream. Unarchiving these events will cause a new, full sync of the table.
  • Archived properties will stop syncing downstream (the column will remain but it will be empty). Unarchiving these properties will cause the property to sync again, but there might be a gap in the table (with no backfill occurring). 
• When a custom event property is seen for the first time, we add a new property column to the corresponding event table.
• When a custom user property is seen for the first time, we add a new user property column to the users table.
• When user-level property values are updated with heap.addUserProperties, we update corresponding rows in the users table.
• When an anonymous user gets identified with an existing identity via heap.identify, we "migrate" the user by running an update on the users table and another update on all event tables that reference the anonymous user's user_id.

Toggle Multiple Events or Segments To Sync

You can toggle multiple events or segments to sync from the Data > Labeled events or Segments page. Click the checkbox next to the event or segment, then click the Sync icon next to x events/segments selected.

You'll be prompted to select your warehouse from the data warehouse drop-down, then confirm that you want to enable the selected events to be synced to the selected warehouse.

Toggle Multiple Properties To Sync/Unsync

You can toggle multiple properties to sync or unsync. Unsyncing properties allows you to prevent the buildup of table cruft downstream, which can impact your sync performance.

To sync or unsync properties, from Data > Properties (event & users), click the checkbox next to the property, then click the sync or unsync icon next to x properties selected.

You can select an entire category by first selecting one property within that category. A checkbox will appear next to the category name which you can then select.

A pop-up will appear where you can select the warehouse(s) to sync or unsync these properties to.

Table Relationships and Joining with Other Data

Joining Heap Connect Tables

Given the hierarchical nature of the data model, joining user information with event data is simple in Heap Connect. All you need to do is join the user table using Heap’s unique user ID with the table(s) you are analyzing.

main_production.users
	JOIN main_production.[event_name] 
		ON main_production.users.user_id = main_production.[event_name].user_id

The same approach can be taken using a combination of the user and session ID by joining the sessions table with any event table(s) of interest.

Joining With Other Data Sets

Similarly, Heap Connect allows you to easily combine user interaction data with data from other sources such as support, marketing automation, or revenue data. We recommend sending an internal user ID shared between these sources via our Identify API, which is then exposed retroactively on the users table in Heap and ready to join with other sources. Usually, you’ll need to join the event and users tables first so that the internal ID is available on the event level.

SELECT main_production.users.email, is_won
	FROM main_production.users 
	JOIN main_production.viewed_customer_page 
    		ON main_production.users.user_id=main_production.viewed_costumer_page.user_id 
	JOIN salesforce_.accounts 
    		ON main_production.users.email=salesforce._account.name

Depending on the structure of your data, this query would show the account email of users who had viewed the customer page and whether or not that contract was won. Analyzing these two sources together can reveal whether or not the customers' page is correlated with the number of deals won and help you answer questions like, “How can my sales team push more prospects to view this documentation?” or “How can I change my page to make it a more valuable resource?”