Create Lakebase-Connected Visualizations in Klipfolio

Klipfolio is an online dashboard platform designed to create real-time business dashboards, whether for your team or clients. When combined with CData Connect AI, you gain immediate cloud-to-cloud access to Lakebase data to create visualizations, reports, and more. This article provides step-by-step instructions on connecting to Lakebase within Connect AI and creating visualizations using Lakebase data in Klipfolio.

CData Connect AI offers a direct cloud-to-cloud interface for Lakebase, enabling you to construct reports from real-time Lakebase data data within Klipfolio—without the need for data replication to a database natively supported by Klipfolio. While building visualizations, Klipfolio generates SQL queries to fetch data. With optimized data processing capabilities out of the box, CData Connect AI efficiently directs all supported SQL operations (such as filters, JOINs, etc.) directly to Lakebase, harnessing server-side processing to swiftly retrieve the requested Lakebase data data.

Configure Lakebase Connectivity for Klipfolio

Connectivity to Lakebase from Klipfolio is made possible through CData Connect AI. To work with Lakebase data from Klipfolio, we start by creating and configuring a Lakebase connection.

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

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

3. Enter the necessary authentication properties to connect to Lakebase. To connect to Databricks Lakebase, start by setting the following properties:
   • DatabricksInstance: The Databricks instance or server hostname, provided in the format instance-abcdef12-3456-7890-abcd-abcdef123456.database.cloud.databricks.com.
   • Server: The host name or IP address of the server hosting the Lakebase database.
   • Port (optional): The port of the server hosting the Lakebase database, set to 5432 by default.
   • Database (optional): The database to connect to after authenticating to the Lakebase Server, set to the authenticating user's default database by default.

   OAuth Client Authentication

   To authenicate using OAuth client credentials, you need to configure an OAuth client in your service principal. In short, you need to do the following:

   1. Create and configure a new service principal
   2. Assign permissions to the service principal
   3. Create an OAuth secret for the service principal

   For more information, refer to the Setting Up OAuthClient Authentication section in the Help documentation.

   OAuth PKCE Authentication

   To authenticate using the OAuth code type with PKCE (Proof Key for Code Exchange), set the following properties:

   • AuthScheme: OAuthPKCE.
   • User: The authenticating user's user ID.

   For more information, refer to the Help documentation.

   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Lakebase 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.

With the connection configured and a PAT generated, you are ready to connect to Lakebase data from Klipfolio.

Connect to Lakebase from Klipfolio

The steps below outline connecting to CData Connect AI from Klipfolio to create a new Lakebase data source.

1. Open Klipfolio
2. Click in Data Sources to add a new data source
3. Search for and select MSSQL as the Service 👁 Adding a new datasource.
   
4. Click "Create a custom MSSQL data source"
5. Configure the data source by setting the MSSQL connection properties:
   • Host: tds.cdata.com
   • Port: 14333
   • Database: your database (e.g., Lakebase1)
   • Driver: MS SQL
   • Username: a Connect AI user (e.g. [email protected])
   • Password: the above user's PAT
   • SQL Query: any query to retrieve data (e.g. SELECT * FROM Orders )
   • Select the checkbox to "Include column headers"
   • Select the checkbox to "Use SSL/TLS"
   👁 Configuring the connection to Connect AI.
   
6. Click "Get data" to preview the Lakebase data before building a data model.

Build a Data Model

After retrieving the data, click the checkbox to "Model your data" and click "Continue." In the new window, configure your data model.

1. Confirm that the model includes all columns you wish to work with
2. Name your model
3. (optional) Set the Description
4. Set "Header in row" to 1
5. Click the toggle to "Exclude data before row" and set the value to 2
6. Click "Save and Exit" 👁 Configuring the data model.
   

Create a Metric

With the data modeled, we are ready to create a Metric (or visualization) of the data to be used in the Klipfolio platform for dashboards, reporting, and more.

1. Click "Create metrics"
2. Select a Data source
3. Select a Metric value and default aggregation
4. Select Segmentation(s)
5. Select a Date & time
6. Select a Data shape
7. Configure the Display settings
8. Click Save 👁 Configuring a Metric
   
9. Navigate to your Metric and further configure the visualization 👁 A configured Metric
   

SQL Access to Lakebase Data from Cloud Applications

Now you have a Metric built from live Lakebase data. You can add it to a new dashboard, share, and more. Easily create more data sources and new visualizations, produce reports, and more — all without replicating Lakebase data.

To get SQL data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications, try CData Connect AI.