Creating Snowflake-Connected Applications in Unqork

Unqork is a completely visual, no-code application development platform that helps large organizations build complex custom software. CData Connect AI exposes Snowflake as a REST endpoint, which you can then query from Unqork with simple HTTP requests. This enables you to create your own custom application with Snowflake data.

You can use CData Connect AI to feed Snowflake data to Unqork. From there you can build custom business applications in a visual, drag-and-drop interface. This article shows how to connect to Snowflake and build workflows with live Snowflake data in Unqork.

Getting Started

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Connect to Snowflake from Unqork

To work with live Snowflake data in Unqork, we need to connect to Snowflake from Connect AI, provide user access to the connection, and create a Workspace for the Snowflake data.

Connect to Snowflake from Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

1. Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a Connection

2. Select "Snowflake" from the Add Connection panel
👁 Selecting a data source

3. Enter the necessary authentication properties to connect to Snowflake.

   To connect to Snowflake:

   1. Set User and Password to your Snowflake credentials and set the AuthScheme property to PASSWORD or OKTA.
   2. Set URL to the URL of the Snowflake instance (i.e.: https://myaccount.snowflakecomputing.com).
   3. Set Warehouse to the Snowflake warehouse.
   4. (Optional) Set Account to your Snowflake account if your URL does not conform to the format above.
   5. (Optional) Set Database and Schema to restrict the tables and views exposed.
   6. (Optional) If MFA is enabled on your Snowflake account (via Duo Security), set MFACode to the passcode generated by your Duo authenticator app.

   See the Getting Started guide in the CData driver documentation for more information.

   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Snowflake Connection page and update the User-based permissions. 👁 Updating permissions
   

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create. 👁 Creating a new PAT
   
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

Configure Snowflake Endpoints for Unqork

After connecting to Snowflake, create a workspace for your desired table(s).

1. Navigate to the Workspaces page and click Add to create a new Workspace (or select an existing workspace). 👁 The Workspaces page.
   👁 Adding a new Workspace.
   
2. Click Add to add new assets to the Workspace.
3. Select the Snowflake connection (e.g. Snowflake1) and click Next. 👁 Selecting an Asset (Salesforce is shown).
   
4. Select the table(s) you wish to work with and click Confirm. 👁 Selecting Tables (Salesforce is shown).
   
5. Make note of the OData Service URL for your workspace, e.g. https://cloud.cdata.com/api/odata/{workspace_name}

With the connection, PAT, and Workspace configured, you are ready to connect to Snowflake data from Unqork.

Create a Simple Application for Snowflake Data

With the OData Endpoint configured for Snowflake through Connect AI, you are ready to create a Snowflake-connected application in Unqork. Here are the basic steps to this process:

• Register Snowflake (via Connect AI) as an Unqork service
• Create a workspace in Unqork
• Create a module-type application

Register Snowflake (via Connect AI) as an Unqork Service

To connect to Connect AI, you need to give your environment permission to connect with an external service. Do this through Services Administration.

1. Click the Settings drop-down at the top right corner of the Unqork Designer Platform.
2. Click Administration.
3. Under Integrations, click Services Administration.
4. Enter a Service Title, for example, Connect AI.
5. Enter a Service Name, for example, cdataConnect.
6. Enter a Service protocol + host. This is the API endpoint you want to reference. For example, https://cloud.cdata.com/api/odata/{workspace_name}.
7. Select Basic Auth from the Type of Authentications drop-down.
8. Enter the Connect AI user ID (e.g. [email protected]) in the User Name field.
9. Enter the Connect AI user PAT in the Password field. 👁 Adding a Service for Connect AI
   
10. Click Add Service.

Create a Workspace

Unqork lets you create your own workspace, which is a virtual container for you and your team to store and organize your applications. Once you build a workspace, you can add applications to it.

To create a workspace:

1. Click Create Workspace
2. Enter a unique Workspace Name
3. Click Create

Your workspace tile appears under the Workspaces tab.

Create a Module-Type Application

With your workspace added, you are ready to create your application. You have the choice between a module-type and workflow-type application. For this use case, make a module-type application.

1. Navigate to the Apps tab from your open workspace.
2. Click Create App.
3. Enter a unique App Name.
4. Select a preview style from the Style drop-down. A style specifies your application's appearance to your and-users. If left blank, your application uses the environment's default style.
5. Select Module from the App Type drop-down.
6. Select New Entrypoint Module from the App Entrypoint Module drop-down.
7. Click Create.

You will land on the Modules tab of your new application. It should look like the following:

👁 The Modules tab of the new application.

Click the title to name the module in the Module Editor.

To complete your application, you need the following components:

• Hidden component: stores the data retrieved by the Plug-In
• Initializer component: executes the Plug-In when displaying tables
• Plug-In component: retrieves Snowflake data through Connect AI and stores it in the Hidden component
• ViewGrid component: creates on HTML table from the data stored in the Hidden component

Configure the Hidden Component

This Hidden component stores the Snowflake data retrieved through Connect AI.

1. Drag and drop a Hidden component onto your canvas.
2. Enter a Property ID and Canvas Label Text.

NOTE: Property IDs must be in Camel Case (stylized as camelCase). For example, hiddenComponent. Since the Hidden component is not visible to and-users, use your Property ID as the Canvas Label Text.

3. Click Save.

Configure the Plug-in Component

Next, add a Plug-In component to request data from Connect AI. This component connects with the service you set up in Services Administration.

1. Drag and drop a Plug-In component onto your canvas, placing it below the Hidden component.
2. Enter a Property ID and Canvas Label Text.

   NOTE: You must use Camel Case (stylized as camelCase). For naming best practices, start your Plug-In's Property ID with plugin. For example, pluginGetAWProducts.

3. Configure the Outputs table as follows:
   • Enter the Property ID of your Hidden component in the Property ID column.
   • Enter value in the Mapping column.
4. Select External as the Service Type
5. From the External Services drop-down, select your Connect AI service. This is the external service you set up in Services Administration.
6. Add the specific endpoint for your Connect AI resources to the and of the Data Sources URL. For example, AdventureWorks2012_Production_Product. 👁 Highlighting a specific endpoint in Connect AI
   

NOTE: Your Data Sources URL will have a value similar to: https://cloud.cdata.com/api/odata/{workspace_name}/AdventureWorks2012_Production_Product.

7. Click Save.

Configure the Initializer Component

The Initializer component is what fires the Plug-In to retrieve your Snowflake data.

1. Drag and drop on Initializer component onto your canvas, placing it above the Plug-In component.
2. Enter a Property ID and Canvas Label Text.

   NOTE: You must use Camel Case (stylized as camelCase). For naming best practices, start your Initializer's Property Name with init. For example, initGetAWProducts.

3. Set New Submission as the Trigger Type.
4. In the Outputs table, enter the following:
   • Enter the Property ID of your Plug-In in the Property ID column's field.
   • Enter trigger in the Type column's field.
   • Enter GO in the Value column's field.
5. Click Save.

Configure the ViewGrid Component

The ViewGrid component references the data stored in your Hidden component. Then, it displays the Snowflake data to your and-users in a dashboard (or table).

1. Drag and drop a ViewGrid component onto your canvas, placing it below the Plug-In component.
2. Enter a Label and Property Name.

   NOTE: You must use Camel Case (stylized as camelCase). For naming best practices, start your ViewGrid's Property Name with vg. For example, vgAWProductView.

3. In the Inputs table, set id to the Property ID of the hidden component.
4. In the Display table:
   • In the id column: enter the IDs of the fields you want to display.
   • In the handing column: enter the title you want for each field. This is how the field will display to your and-users.
   👁 Configuring the ViewGrid Inputs and Display
   
5. Click Save.
6. Save your module.

Once you add and configure the above components, you can preview how your application looks to and-users. In the Module Editor, click Preview Module to see the front-facing view (or "Express View") of the module.

Your Express View module should look something like this:

👁 Previewing the Module

More Information & Free Trial

With Connect AI and Unqork, you can easily build Snowflake-connected applications. Request a free trial of Connect AI and start working with Snowflake data in Unqork today.