Create Reports from Amazon S3 Data in Looker Studio

Looker Studio, formerly known as Google Data Studio, empowers users to craft customized reports featuring data visualizations that can be shared with clients while reflecting your brand identity. When combined with CData Connect AI, you gain immediate cloud-to-cloud access to Amazon S3 data to create visualizations, dashboards, and more. This article provides step-by-step instructions on establishing a virtual database for Amazon S3 and generating reports from Amazon S3 data within Looker Studio.

CData Connect AI offers a seamless cloud-to-cloud interface tailored for Amazon S3, making it straightforward to construct reports directly from live Amazon S3 data within Looker Studio without the need for data replication. As you create visualizations, Looker Studio generates queries to retrieve data. With its inherent optimized data processing capabilities, CData Connect AI efficiently channels all supported query operations, including filters, JOINs, and more, directly to Amazon S3. This leverages server-side processing to swiftly provide the requested Amazon S3 data.

Configure Amazon S3 Connectivity for Looker Studio

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

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

2. Select "Amazon S3" from the Add Connection panel
👁 Selecting a data source

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.

   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Amazon S3 Connection page and update the User-based permissions. 👁 Updating permissions
   

With the connection configured, you are ready to connect to Amazon S3 data from Looker Studio.

Visualize Live Amazon S3 Data from Looker Studio

The steps below outline connecting to CData Connect AI from Looker Studio to create a new Amazon S3 data source and build a simple visualization from the data.

1. Log into Looker Studio, click data sources, create a new data source, and choose CData Connect AI Connector.
👁 Create a new connection in Looker Studio

2. Click Authorize and allow access to your Google account. 👁 Granting permissions to the Connector
   
3. Click Authorize to authenticate with your CData Connect AI instance 👁 Authenticating with CData Connect AI
   
4. In the CData Connect AI Connector in Looker Studio select Connections to import from the dropdown and click Next
👁 Importing from Connections

5. Now select a Connection (e.g. AmazonS31) and click Next 👁 Selecting a Connection
   
6. Select a Table (e.g. ObjectsACL) or use a Custom Query and click Connect to continue 👁 Selecting a Table
   
7. If needed, modify columns, click Create Report, and add the data source to the report.
👁 Configuring column definitions

8. Select a visualization style and add it to the report.
9. Select Dimensions and Measures to customize your visualization.
👁 Visualizing Amazon S3 data in Looker Studio

Live Access to Amazon S3 Data from Cloud Applications

Now you have a direct, cloud-to-cloud connection to live Amazon S3 data from your Looker Studio workbook. You can create more data sources and new visualizations, build reports, and more — all without replicating Amazon S3 data.

Try CData Connect AI and get real-time data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications.