This article is part of a series on the Snowflake integration:

Planhat's Snowflake integration enables you to sync CRM (static) data bidirectionally, and time-series usage data from Snowflake to Planhat. Data is synced automatically, on a fast, regular cadence.

With your Snowflake data in Planhat, you can leverage Planhat’s workflow platform to take data-driven action, to drive long-term value for your customers and improve internal efficiency. In addition, you can consolidate Snowflake data with additional data types, such as tickets or emails, to give your team a complete 360° view of your customers. You can also quickly and easily perform advanced data analysis and visualise your Snowflake data, helping your team proactively identify risks and opportunities to retain and grow customer revenue.

Here's a summary of some key specifications related to the Snowflake integration; we discuss these in further detail in this article.

*Note: Data cannot be synced from Planhat back to Snowflake views, as views are built on the fly in Snowflake.

There are two main stages to setting up the Snowflake integration:

CRM data can be synced automatically, both to and from Snowflake, on an hourly basis.

To enable the automatic sync, turn on the toggle switch "activate Snowflake automation synchronization" at the top of the integration.

Before you do this, ensure that "change_tracking" is turned on in Snowflake (for each relevant table/view). You should also do a manual full sync (via the "Full sync" button) to set the baseline and enable the integration to detect that change tracking is on.

The automatic sync every hour is a partial sync - syncing new/updated data.

If you don't enable the automatic synchronisation of CRM data, you can sync manually via the "Full sync" button, or using the arrow symbols at the right of each sync section. These are full syncs rather than partial syncs.

You can set Planhat to fetch usage data from Snowflake every 5, 10, 30, or 60 minutes, or daily at a specified time.

For both CRM data and usage data, the integration uses unique IDs for data mapping. You may hear these referred to as keys, keyables, IDs or identifiers.

The requirements for these unique IDs are slightly different for CRM data compared to usage data.

When configuring CRM data mapping, for each sync section (Planhat data model), you select an ID for both the Planhat side and the Snowflake side.

The Planhat ID could be Source ID or External ID, or email address in some cases. These are fields on the Planhat models, containing a unique ID to specify that particular record (e.g. the Company record for Apple).

For the ID on the Snowflake side, select a suitable column from the dropdown menu. The ID/key must be unique and text fields.

(For CRM data, in order for Planhat to fetch updates from Snowflake, you need to enable "change_tracking" for the relevant table or view in Snowflake. This is necessary so the integration can identify what's changed, and implement the automatic partial sync that runs when you enable the "activate Snowflake automation synchronization" toggle switch.)

When it comes to the one-way sync of usage data (time-series data), there are some differences:

Rows in Snowflake must be identified by a unique, numeric, incrementing column for the ID (key).

If there are any errors with authorisation or sync (for example, if your Snowflake token has expired), they are surfaced in the Snowflake integration.

There are also detailed logs available within the integration, so you can see what actions have occurred and when.

This means it's easy for you to investigate and resolve any issues. You can refer to our troubleshooting article for further guidance. Your TAM/CSM and our Support team would be happy to help if you require any additional advice.