Integrate Live Certinia Data into Amazon SageMaker Canvas with RDS
Amazon SageMaker Canvas is a no-code machine learning platform that lets you generate predictions, prepare data, and build models without writing code. When paired with CData Connect AI, you get instant, cloud-to-cloud access to Certinia data for building custom machine-learning models, predicting customer churn, generating texts, building chatbots, and more. This article shows how to connect to Connect AI from Amazon SageMaker Canvas using the RDS connector and integrate live Certinia data into your ML model deployments.
CData Connect AI provides a pure SQL, cloud-to-cloud interface for Certinia, allowing you to easily integrate with live Certinia data in Amazon SageMaker Canvas — without replicating the data. CData Connect AI looks exactly like a SQL Server database to Amazon SageMaker Canvas and uses optimized data processing out of the box to push all supported SQL operations (filters, JOINs, etc) directly to Certinia, leveraging server-side processing to quickly return Certinia data.
Configure Certinia Connectivity for Amazon SageMaker Canvas
Connectivity to Certinia from Amazon SageMaker Canvas is made possible through CData Connect AI. To work with Certinia data from Amazon SageMaker Canvas, we start by creating and configuring a Certinia connection.
- Log into Connect AI, click Sources, and then click Add Connection
- Select "Certinia" from the Add Connection panel
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Enter the necessary authentication properties to connect to Certinia.
There are several authentication methods available for connecting to Certinia: login credentials, SSO, and OAuth.
Authenticating with a Login and Token
Set the User and Password to your login credentials. Additionally, set the SecurityToken. By default, the SecurityToken is required, but you can make it optional by allowing a range of trusted IP addresses.
To disable the security token:
- Log in to Certinia and enter "Network Access" in the Quick Find box in the setup section.
- Add your IP address to the list of trusted IP addresses.
To obtain the security token:
- Open the personal information page on certinia.com.
- Click the link to reset your security token. The token will be emailed to you.
- Specify the security token in the SecurityToken connection property or append it to the Password.
Authenticating with OAuth
If you do not have access to the user name and password or do not want to require them, use the OAuth user consent flow. See the OAuth section in the Help for an authentication guide.
Connecting to Certinia Sandbox Accounts
Set UseSandbox to true (false by default) to use a Certinia sandbox account. Ensure that you specify a sandbox user name in User.
- Click Save & Test
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Navigate to the Permissions tab in the Add Certinia Connection page and update the User-based 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.
- Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
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Give the PAT a name and click Create.
- 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 Certinia data from Amazon SageMaker Canvas.
Connecting to CData Connect AI from Amazon SageMaker Canvas
With the connection in CData Connect AI configured, you are ready to integrate live Certinia data into Amazon SageMaker Canvas using its RDS connector.
- Select a domain and user profile in Amazon SageMaker Canvas and click on "Open Canvas".
- Once the Canvas application opens, navigate to the left panel, and select "My models".
- Click on "Create new model" in the My models screen.
- Specify a Model name in Create new model window and select a Problem type. Click on "Create".
- Once the model version gets created, click on "Create dataset" in the Select dataset tab.
- In the Create a tabular dataset window, add a "Dataset name" and click on "Create".
- Click on the "Data Source" drop-down and search for or navigate to the RDS connector and click on " Add Connection".
- In the Add a new RDS connection window, set the following properties:
- Connection Name: a relevant connection name
- Set Engine type to sqlserver-web
- Set Port to 14333
- Set Address as tds.cdata.com
- Set Username to a Connect AI user (e.g. [email protected])
- Set Password to the PAT for the above user
- Set Database name the Certinia connection (e.g., Certinia1)
- Click on "Create connection".
Integrating Certinia Data into Amazon SageMaker Canvas
With the connection to Connect AI configured in the RDS, you are ready to integrate live Certinia data into your Amazon SageMaker Canvas dataset.
- In the tabular dataset created in RDS with Certinia data, search for the Certinia connection configured on Connect AI in the search bar or from the list of connections.
- Select the table of your choice from Certinia, drag and drop it into the canvas on the right.
- You can create workflows by joining any number of tables from the Certinia connection (as shown below). Click on "Create dataset".
- Once the dataset is created, click on "Select dataset" to build your model.
- Perform analysis, generate prediction, and deploy the model.
At this point, you have access to live Certinia data in Amazon SageMaker that you can utilize to build custom ML models to generate predictive business insights and grow your organization.
SQL Access to Certinia Data from Cloud Applications
Now you have a direct connection to live Certinia data from Amazon SageMaker Canvas. You can create more connections, datasets, and predictive models to drive business — all without replicating Certinia data.
To get real-time data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications, see the CData Connect AI.