Build Amazon S3-Connected Visualizations in datapine

datapine is a browser-based business intelligence platform. When paired with the CData Connect Cloud, you get access to your Amazon S3 data directly from your datapine visualizations and dashboards. This article describes connecting to Amazon S3 in CData Connect Cloud and building a simple Amazon S3-connected visualization in datapine.

CData Connect Cloud provides a pure SQL Server interface for Amazon S3, allowing you to query data from Amazon S3 without replicating the data to a natively supported database. Using optimized data processing out of the box, CData Connect Cloud pushes all supported SQL operations (filters, JOINs, etc.) directly to Amazon S3, leveraging server-side processing to return the requested Amazon S3 data quickly.

Configure Amazon S3 Connectivity for datapine

Connectivity to Amazon S3 from datapine is made possible through CData Connect Cloud. To work with Amazon S3 data from datapine, we start by creating and configuring a Amazon S3 connection.

1. Log into Connect Cloud, click Connections and click Add Connection
2. Select "Amazon S3" from the Add Connection panel
3. Enter the necessary authentication properties to connect to Amazon S3.

   To authorize Amazon S3 requests, provide the credentials for an administrator account or for an IAM user with custom permissions. Set AccessKey to the access key Id. Set SecretKey to the secret access key.

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

   For information on obtaining the credentials and other authentication methods, refer to the Getting Started section of the Help documentation.

4. Click Create & Test
5. Navigate to the Permissions tab in the Add Amazon S3 Connection page and update the User-based permissions.

Add a Personal Access Token

If you are connecting from a service, application, platform, or framework that does not support OAuth authentication, you can create a Personal Access Token (PAT) to use for authentication. Best practices would dictate that you create a separate PAT for each service, to maintain granularity of access.

1. Click on your username at the top right of the Connect Cloud app and click User Profile.
2. On the User Profile page, scroll down to the Personal Access Tokens section and click Create PAT.
3. Give your PAT a name and click Create.
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

Connecting to Amazon S3 from datapine

Once you configure your connection to Amazon S3 in Connect Cloud, you are ready to connect to Amazon S3 from datapine.

1. Log into datapine
2. Click Connect to navigate to the "Connect" page
3. Select MS SQL Server as the data source
4. In the Integration step, fill in the connection properties and click "Save and Proceed"
   • Set the Internal Name
   • Set Database Name to the name of the connection we just configured (e.g. AmazonS31)
   • Set Host / IP to "tds.cdata.com"
   • Set Username to your Connect Cloud username (e.g. user@mydomain.com)
   • Set Password to the corresponding PAT
   • Set Database Port to "14333"
5. In the Data Schema step, select the tables and fields to visualize and click "Save and Proceed"
6. In the References step, define any relationships between your selected tables and click "Save and Proceed"
7. In the Data Transfer step, click "Go to Analyzer"

Visualize Amazon S3 Data in datapine

After connecting to CData Connect Cloud, you are ready to visualize your Amazon S3 data in datapine. Simply select the dimensions and measures you wish to visualize!

Having connect to Amazon S3 from datapine, you are now able to visualize and analyze real-time Amazon S3 data no matter where you are. To get live data access to 100+ SaaS, Big Data, and NoSQL sources directly from datapine, try CData Connect Cloud today!