This article provides a complete overview of how Admins can create Datasets in Data Designer by fetching data from Snowflake as a data source.
Business Use Case: If your organization’s IT infrastructure uses Snowflake to store business data, this connection helps you build reports on this data in Gainsight and combine this data with other customer information and create datasets in Data Designer.
- Create a Snowflake connection in the Connectors 2.0 page, to connect the Snowflake data to Gainsight. For more information on creating a Snowflake connection, refer to the Snowflake Integration article.
- Gainsight has the capability to pull data exceeding 5GB using the Snowflake connector, provided you grant the permission of 'create stage' on the schema.
Create Snowflake Dataset
To create Snowflake Dataset:
- Navigate to Administration > Data Designer. You will land on the Design List page.
- Click New Design. The New Design page appears where you can see 4 tabs:
Enter the following information in the Details tab:
- Design Name: Enter the name of the Data Design.
- Select Folder: Select the folder that you have already created in the Design List page, or by default, the design is saved in the Uncategorized folder.
- Description (Optional): Enter the details in the Description textbox as required.
- Click Prepare. You will be navigated to the Preparation tab.
Preparation of Dataset
To prepare a Dataset:
- From the Data Source dropdown list, select the required Snowflake data source. You can see all the objects available under the selected Snowflake source.
Note: You can see the Snowflake data source here if you have established a Snowflake connection in the Connectors 2.0 page as shown in the Prerequisites.
- Drag and Drop the required objects from the left pane to the canvas screen. The Select Fields window appears.
In this section, all the fields available for the source object are displayed.
To select Fields:
- Select the required fields you want to add to the dataset and click Select. You will land on the Object page. This page displays 3 tabs:
- Details & Summary
Details and Summary Tab
The following options are available in the Details & Summary tab:
- Object Name: Displays the Original Name of the Object that a specific Dataset is built on.
- Output Dataset Name: In the Output Dataset Name textbox, type In the Dataset Name, if you want to edit the Dataset Name.
- Description: Enter the Description of the Dataset as required.
- Fields & Filters: You can view a list of all Fields (including Group By, if any) and Filters in the Dataset.
This displays the following information:
- Fields: The name of the fields selected in the above step.
- Group By: You can select the required fields to Group By, to slice and dice the data in the dataset. Once you select a Field to Group By, all the other fields in the dataset will become aggregated.
- Aggregation: You can select the required aggregation type from the Aggregation dropdown list.
- Display Name: By default, the Field Name name appears in the Display Name textbox, if required you can modify it. Display Names are shown in the Datasets/reports.
- Click Add Fields, if additional fields are to be added.
- Click the Settings/Gear icon to make changes to numeric data type fields. For more information refer to the Preparation details in Data Designer article.
- Click the Delete/Trash icon to delete the field from the dataset.
- Click Save.
To apply Filters:
- Navigate to the Filters tab.
- Click Add Filter.
- From the dropdown list of Field, select the Field to which filter is to be applied.
- Choose the Operator and then input the data in the Value textbox.
- You can also Add more filters by clicking the + icon next to Value textbox.
- You can Delete a filter by clicking the x icon.
- You can add advance filters such as (A OR B) AND C, type in your desired expression in the Advanced Logic text box.
- Click Save.
To edit a Dataset:
Click the Pencil icon (or) click the Context menu, and then click Edit to edit a dataset. You will land on the following page as shown below.
Edit the Output Dataset Name, Description, Fields, and Filters as required.
You can also create more Datasets from Salesforce, MDA data, Amazon S3, and Snowflake, and perform Merge, Transform, and other actions on the created Datasets. Then, you can proceed to the Explore tab to analyze the data and create reports.
- For information on how to edit, merge, or transform the datasets, refer to the Preparation Details in Data Designer article.
- For information on how to explore a dataset, refer to the Explore Details in Data Designer article.
- For information on how to create a dataset, refer to the Create Datasets in Data Designer article.
- For information on the most frequently asked questions on Data Designer, refer to the Data Designer FAQs article.