Amazon Redshift

Overview

HockeyStack’s Amazon Redshift integration allows you to seamlessly sync data from your Redshift tables into HockeyStack. By ensuring that your tables are set up according to our guidelines, you can leverage your Redshift data for deeper insights and analysis within the HockeyStack platform.

Connecting HockeyStack to Amazon Redshift

Connecting HockeyStack to Amazon Redshift is a straightforward process. You’ll need to prepare a table with the required structure and then provide secure access credentials, along with a description of the columns you plan to sync.

Step 1: Prepare the Table

To ensure a smooth syncing process, set up the Redshift table you want HockeyStack to read from with the following guidelines:

Required Columns:
- Timestamp: A column representing the timestamp of each record (e.g., the date/time of the action).
- Identity (Email): A unique identifier that allows HockeyStack to associate the record with a specific user or entity.
- Other Action Data: Any additional columns that represent meaningful user actions or attributes you want to analyze.
Incremental Sync Support: HockeyStack uses an internal Last Sync Date to determine which rows to ingest.
- Include an Added or Updated At column if you plan to insert historical data or backdate your rows. This ensures that HockeyStack can correctly pick up any new or modified rows that fall before the current Last Sync Date.

Step 2: Provide Access Credentials

After preparing the table, you’ll need to share credentials so HockeyStack can securely access your Redshift instance. We recommend using a dedicated read-only Redshift user account. When providing credentials, also include:

A Short Column Description: For each column in the target table, provide a brief explanation of what the data represents. For example:
- timestamp: The date and time the event occurred.
- email: The user’s email address, serving as a unique identifier.
- page_view_count: The number of pages viewed by the user.
- added_at or updated_at: The datetime when the row was created or last updated in Redshift.

This step ensures HockeyStack can correctly interpret and map your data to the platform’s schema, making it more valuable and actionable.

Once these steps are completed, HockeyStack’s support team will configure the integration. After setup, HockeyStack will begin syncing your Redshift data on the agreed-upon schedule (often daily), enabling you to track, analyze, and activate your customer insights more effectively.

If you have questions, need guidance on column selection, or want to discuss best practices for syncing historical and ongoing data, our team is here to help.

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Last updated 5 months ago

Connecting HockeyStack to Amazon Redshift

Step 1: Prepare the Table

To ensure a smooth syncing process, set up the Redshift table you want HockeyStack to read from with the following guidelines:

Required Columns:

Timestamp: A column representing the timestamp of each record (e.g., the date/time of the action).
Identity (Email): A unique identifier that allows HockeyStack to associate the record with a specific user or entity.
Other Action Data: Any additional columns that represent meaningful user actions or attributes you want to analyze.

Incremental Sync Support: HockeyStack uses an internal Last Sync Date to determine which rows to ingest.

Include an Added or Updated At column if you plan to insert historical data or backdate your rows. This ensures that HockeyStack can correctly pick up any new or modified rows that fall before the current Last Sync Date.

Step 2: Provide Access Credentials

A Short Column Description: For each column in the target table, provide a brief explanation of what the data represents. For example:

timestamp: The date and time the event occurred.
email: The user’s email address, serving as a unique identifier.
page_view_count: The number of pages viewed by the user.
added_at or updated_at: The datetime when the row was created or last updated in Redshift.

This step ensures HockeyStack can correctly interpret and map your data to the platform’s schema, making it more valuable and actionable.

If you have questions, need guidance on column selection, or want to discuss best practices for syncing historical and ongoing data, our team is here to help.