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URL: https://www.cdata.com/kb/tech/athena-cloud-thoughtspot.rst

⇱ Model, Search, and Visualize Live Amazon Athena Data in ThoughtSpot

Model, Search, and Visualize Live Amazon Athena Data in ThoughtSpot

👁 Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Use CData Connect AI to connect to live Amazon Athena data for modeling, searching, and visualizing.

ThoughtSpot is a cloud-based analytics platform that uses artificial intelligence (AI) and natural language processing (NLP) to help users analyze data and make decisions. When paired with CData Connect AI, you get instant, cloud-to-cloud access to Amazon Athena data for visualizations, dashboards, and more. This article shows how to connect to Amazon Athena and build visualizations from Amazon Athena data in ThoughtSpot.

About Amazon Athena Data Integration

CData provides the easiest way to access and integrate live data from Amazon Athena. Customers use CData connectivity to:

  • Authenticate securely using a variety of methods, including IAM credentials, access keys, and Instance Profiles, catering to diverse security needs and simplifying the authentication process.
  • Streamline their setup and quickly resolve issue with detailed error messaging.
  • Enhance performance and minimize strain on client resources with server-side query execution.

Users frequently integrate Athena with analytics tools like Tableau, Power BI, and Excel for in-depth analytics from their preferred tools.

To learn more about unique Amazon Athena use cases with CData, check out our blog post: https://www.cdata.com/blog/amazon-athena-use-cases.


Getting Started


CData Connect AI provides a pure SQL Server, cloud-to-cloud interface for Amazon Athena, allowing you to easily build models and visualizations from live Amazon Athena data in ThoughtSpot. As you build visualizations, ThoughtSpot generates SQL queries to gather data. Using optimized data processing out of the box, CData Connect AI pushes all supported SQL operations (filters, JOINs, etc) directly to Amazon Athena, leveraging server-side processing to quickly return Amazon Athena data.

Configure Amazon Athena Connectivity for ThoughtSpot

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

  1. Log into Connect AI, click Sources, and then click Add Connection
    2. 👁 Adding a Connection
  2. Select "Amazon Athena" from the Add Connection panel
    3. 👁 Selecting a data source
  3. Enter the necessary authentication properties to connect to Amazon Athena.

    Authenticating to Amazon Athena

    To authorize Amazon Athena requests, provide the credentials for an administrator account or for an IAM user with custom permissions: Set to the access key Id. Set to the secret access key.

    Note: Though you can connect as the AWS account administrator, it is recommended to use IAM user credentials to access AWS services.

    Obtaining the Access Key

    To obtain the credentials for an IAM user, follow the steps below:

    1. Sign into the IAM console.
    2. In the navigation pane, select Users.
    3. To create or manage the access keys for a user, select the user and then select the Security Credentials tab.

    To obtain the credentials for your AWS root account, follow the steps below:

    1. Sign into the AWS Management console with the credentials for your root account.
    2. Select your account name or number and select My Security Credentials in the menu that is displayed.
    3. Click Continue to Security Credentials and expand the Access Keys section to manage or create root account access keys.

    Authenticating from an EC2 Instance

    If you are using the CData Data Provider for Amazon Athena 2018 from an EC2 Instance and have an IAM Role assigned to the instance, you can use the IAM Role to authenticate. To do so, set to true and leave and empty. The CData Data Provider for Amazon Athena 2018 will automatically obtain your IAM Role credentials and authenticate with them.

    Authenticating as an AWS Role

    In many situations it may be preferable to use an IAM role for authentication instead of the direct security credentials of an AWS root user. An AWS role may be used instead by specifying the . This will cause the CData Data Provider for Amazon Athena 2018 to attempt to retrieve credentials for the specified role. If you are connecting to AWS (instead of already being connected such as on an EC2 instance), you must additionally specify the and of an IAM user to assume the role for. Roles may not be used when specifying the and of an AWS root user.

    Authenticating with MFA

    For users and roles that require Multi-factor Authentication, specify the and connection properties. This will cause the CData Data Provider for Amazon Athena 2018 to submit the MFA credentials in a request to retrieve temporary authentication credentials. Note that the duration of the temporary credentials may be controlled via the (default 3600 seconds).

    Connecting to Amazon Athena

    In addition to the and properties, specify , and . Set to the region where your Amazon Athena data is hosted. Set to a folder in S3 where you would like to store the results of queries.

    If is not set in the connection, the data provider connects to the default database set in Amazon Athena.

    👁 Configuring a connection (Salesforce is shown)
  4. Click Save & Test
  5. Navigate to the Permissions tab in the Add Amazon Athena 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 Amazon Athena data from ThoughtSpot.

Model, Search, and Visualize Live Amazon Athena Data in ThoughtSpot

To establish a connection from ThoughtSpot to the CData Connect AI Virtual SQL Server API, follow these steps.

  1. Log into ThoughtSpot
  2. On the top navigation bar, click Data.
  3. Click Create new > Connection. 👁 Creating a new connection.
  4. Name the connection and click "SQL Server" as the data warehouse. 👁 Selecting SQL Server as the connection type.
  5. Click Continue on the top right.
  6. Enter the connection settings:
    • Host: enter the Virtual SQL Server endpoint: tds.cdata.com
    • Port: : enter 14333
    • Username: enter your CData Connect AI username. This is displayed in the top-right corner of the CData Connect AI interface. For example, [email protected].
    • Password: enter the PAT you generated on the Settings page.
    • Database: enter the Connection Name of the CData Connect AI data source you want to connect to (for example, AmazonAthena1).
    👁 Configuring the connection to the Virtual SQL Server API
  7. Click Continue.
  8. After connecting successfully, you will be able to choose which tables to include. 👁 Selecting tables (Salesforce is shown).
  9. Click Create Connection.

After you successfully configure your connection, you can build models, search, and visualize your Amazon Athena data.

Real-Time Access to Amazon Athena Data from Cloud Applications

At this point, you have a direct, cloud-to-cloud connection to live Amazon Athena data from ThoughtSpot. You can model, search, and visualize your data from ThoughtSpot . For more information on gaining live access to data from more than 100 SaaS, Big Data, and NoSQL sources from cloud applications like ThoughtSpot, refer to our Connect AI page.