Integrate Live Cvent 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 Cvent 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 Cvent data into your ML model deployments.
CData Connect AI provides a pure SQL, cloud-to-cloud interface for Cvent, allowing you to easily integrate with live Cvent 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 Cvent, leveraging server-side processing to quickly return Cvent data.
Configure Cvent Connectivity for Amazon SageMaker Canvas
Connectivity to Cvent from Amazon SageMaker Canvas is made possible through CData Connect AI. To work with Cvent data from Amazon SageMaker Canvas, we start by creating and configuring a Cvent connection.
- Log into Connect AI, click Sources, and then click Add Connection
- Select "Cvent" from the Add Connection panel
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Enter the necessary authentication properties to connect to Cvent.
Before you can authenticate to Cvent, you must create a workspace and an OAuth application.
Creating a Workspace
To create a workspace:
- Sign into Cvent and navigate to App Switcher (the blue button in the upper right corner of the page) >> Admin.
- In the Admin menu, navigate to Integrations >> REST API.
- A new tab launches for Developer Management. Click on Manage API Access in the new tab.
- Create a Workspace and name it. Select the scopes you would like your developers to have access to. Scopes control what data domains the developer can access.
- Choose All to allow developers to choose any scope, and any future scopes added to the REST API.
- Choose Custom to limit the scopes developers can choose for their OAuth apps to selected scopes. To access all tables exposed by the driver, you need to set the following scopes:
event/attendees:read event/attendees:write event/contacts:read event/contacts:write event/custom-fields:read event/custom-fields:write event/events:read event/events:write event/sessions:delete event/sessions:read event/sessions:write event/speakers:delete event/speakers:read event/speakers:write budget/budget-items:read budget/budget-items:write exhibitor/exhibitors:read exhibitor/exhibitors:write survey/surveys:read survey/surveys:write
Creating an OAuth Application
After you have set up a Workspace and invited them, developers can sign up and create a custom OAuth app. See the Creating a Custom OAuth Application section in the Help documentation for more information.
Connecting to Cvent
After creating an OAuth application, set the following connection properties to connect to Cvent:
- InitiateOAuth: GETANDREFRESH. Used to automatically get and refresh the OAuthAccessToken.
- OAuthClientId: The Client ID associated with the OAuth application. You can find this on the Applications page in the Cvent Developer Portal.
- OAuthClientSecret: The Client secret associated with the OAuth application. You can find this on the Applications page in the Cvent Developer Portal.
- Click Save & Test
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Navigate to the Permissions tab in the Add Cvent 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 Cvent 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 Cvent 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 Cvent connection (e.g., Cvent1)
- Click on "Create connection".
Integrating Cvent Data into Amazon SageMaker Canvas
With the connection to Connect AI configured in the RDS, you are ready to integrate live Cvent data into your Amazon SageMaker Canvas dataset.
- In the tabular dataset created in RDS with Cvent data, search for the Cvent connection configured on Connect AI in the search bar or from the list of connections.
- Select the table of your choice from Cvent, drag and drop it into the canvas on the right.
- You can create workflows by joining any number of tables from the Cvent 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 Cvent 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 Cvent Data from Cloud Applications
Now you have a direct connection to live Cvent data from Amazon SageMaker Canvas. You can create more connections, datasets, and predictive models to drive business — all without replicating Cvent 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.