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In This Article
Snowflake direct access allows you to access the raw training data associated with your account. In turn, you can import Seismic Learning data into BI tools in order to build custom reports or dashboards, or combine training data with data from other sources such as you CRM.
Two Kinds of Snowflake Access
Customers with a Snowflake instance can take advantage of Snowflake’s data share feature. In essence, this enables data to be shared directly from Seismic's Snowflake instance to the customer’s Snowflake instance. This is the preferred method of access.
Customers without a Snowflake instance can obtain their raw data via read-only Snowflake credentials. These credentials allow customers to ingest data into their BI tool directly from Seismic’s Snowflake instance. If your BI tool can query Snowflake directly or import data from Snowflake, Seismic requires that read-only customers import the data.
Who Should Use This Feature?
Customers considering this feature should ask themselves two questions:
1. Do I have the resources to take advantage of this feature?
In order to make use of Snowflake direct access, a customer will need to have either their own BI tool capable of integrating with Snowflake, their own Snowflake instance, or both. For customers that are using a BI tool that operates only through direct queries, they will have to have their own Snowflake instance as their BI tool will not meet the usage criteria outlined for read-only customers as outlined in the overview section above.
Additionally, a customer will need an analyst (or someone in a similar role) with the time and expertise to set up the data import, create reports and maintain those reports going forward. Seismic Learning will provide documentation and information on the data model, but customers will be responsible for building and maintaining their reports.
2. What do I want to do with the data?
Snowflake direct access will be most useful for customers who want to import learning data into their own BI tool to (1) combine their learning data with data from another source such as a CRM, or (2) build custom reports in the BI tool that will be shown to a restricted audience.
If a customer wants to create custom reports or dashboards, or export .csv files of data for manipulation in a tool like Google Sheets or Excel, using the Sisense dashboards embedded in the application will be simpler, more accessible, and more user-friendly.
How to Gain Access
Customers with their own Snowflake instance need to relay their request to their Account Manager. The AM will provide them with instructions for submitting a request form within the Snowflake Data Marketplace. Once the request has been submitted, Seismic will set up the connection, and the appropriate customer data will begin begin flowing from Seismic’s Snowflake instance to the customer’s Snowflake instance.
Customers without their own Snowflake instance also need to relay their request to their Account Manager. The AM will get Snowflake credentials for the customer, and the customer can then use these credentials to log into Snowflake and configure an integration with their BI tool. For customers utilizing this option, it is crucial they understand that, if their BI tool provides an option for direct query to Snowflake or to import data from Snowflake, they are required to import the data.
Data Model
Below is a diagram of the Seismic Learning data model.
Pointers and Best Practices
Data is organized on the organizational level. For companies with multiple Learning accounts, data for all companies within the organization will be available via an individual Snowflake integration.
Important Table and Field Notes
Table: LEARNINGPROGRESS
LEARNINGPROGRESS is the root table for all learning. It contains all assigned and voluntary lessons and path progress.
To get the most recent progresses filter by
ISLATEST = TRUE
To see only assigned or voluntary progress filter by
ASSIGNEDORVOLUNTARY
ISINHERITEDASSIGNMENT
is a unique field. This field applies to lesson progresses specifically. It is set to TRUE when the lesson progress is the result of the user taking an assigned path. It is set to FALSE when the lesson progress is the result of a direct lesson assignment. This field is also FALSE for path progresses and voluntary lesson progresses.When counting assignments, count
ASSIGNMENTID
and filter byISLATEST = TRUE
ISINHERITEDASSIGNMENT = FALSE
ASSIGNEDORVOLUNTARY = 'Assigned'
Additional helpful filters:
PROGRESSSTATUS
OVERDUESTATUS
To see incomplete + overdue assignments:
PROGRESSSTATUS <> "Complete" and OVERDUESTATUS = "Overdue"
To see completed late assignments:
PROGRESSSTATUS = "Complete" and OVERDUESTATUS = "Overdue"
Table: DAILYACTIVEUSERS
To get the active user count, use
DAILYACTIVEUSERS
and countUSERID
and filter byINCLUDESLESSONLYACTIVITY = TRUE
Optional - filter by date range using
DATE
Table: PATHCONTENTS
This table lists the lessons contained within each path. It can be used in conjunction with LEARNINGPROGRESS to filter down lesson progresses to those contained within a specific path(s).
📝 Note: this table does not account for the user having a progress for the path.
For example, suppose Sam takes the lesson “Intro to Seismic” via the Learn tab. That lesson is also included in the path “Welcome to Seismic.” Sam’s progress for “Intro to Seismic” would be returned in the results even though Sam did not take the lesson directly via the path. The progress is returned because the path contains that lesson.
Frequently Asked Questions
Q. How often does the Snowflake integration sync?
A. Data is refreshed daily. For US tenants, sync begins at 0600 UTC. For EU tenants, 2300 UTC. For AU tenants, 1500 UTC.
Questions? Contact the Support team at support@lessonly.com