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April 20, 2023|
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Introduction
Amazon AppFlow is a service provided by AWS that enables secure and managed data transfer between various SaaS applications and AWS services.
Benefits of Amazon AppFlow
One of the key benefits of AppFlow is its ease of use. A simple point-and-click interface allows you to set up data transfers between applications without coding or scripting. The visual flow builder in the AppFlow console allows you to define the source and destination of the data transfer, map data fields, and set up transformations and filters to modify the data as it moves between applications.
Another important feature of AppFlow is its security and compliance. AppFlow uses industry-standard encryption and security controls to protect your data in transit and at rest. AppFlow also integrates with AWS Identity and Access Management (IAM) to enable fine-grained access control for data transfers.
AppFlow also offers flexibility in terms of data destinations. You can transfer data to various AWS services, including Amazon S3, Amazon Redshift, Amazon EMR, and Amazon DynamoDB, as well as to third-party services like Snowflake and Databricks. This flexibility allows you to store and analyze your data in the way that best suits your needs.
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Use Case
One use case for Amazon AppFlow is transferring data from Google Analytics to Amazon S3. This can be useful for storing and analyzing web analytics data in a secure and scalable way. Here’s how you can use AppFlow to transfer data from Google Analytics to S3:
Set up a connection to Google Analytics in AppFlow: In the AppFlow console, create a connection to your Google Analytics account using OAuth 2.0 authentication. This will allow AppFlow to access your Google Analytics data securely.
Configure a flow in AppFlow: A flow is a set of instructions that defines how data should be transferred between two applications. In this case, you will configure a flow that transfers data from Google Analytics to S3. You can use the visual flow builder in the AppFlow console to configure the flow.
Define the source and destination of the data transfer: In the flow, specify Google Analytics as the source application and S3 as the destination. You can also specify the specific data you want to transfer, such as page views, sessions, or conversion rates.
Map the data fields: Map the data fields from Google Analytics to the corresponding fields in your S3 bucket. This will ensure that the data is stored in the correct format in S3.
Test and activate the flow: To ensure the data is transferred correctly. Once you are satisfied, activate the flow to start transferring data regularly.
Demo on transferring Google Analytics data to Amazon S3 using Amazon AppFlow
Step 1: Create a property under Admin in the Google Analytics account
Note: Tagging-do the tagging based on the requirement while creating property
Step 2: Once you create property and tags, it will show the tags like this.
Step 3: On the Google API Console (login here https://console.developers.google.com), Select Library.
- Enter analytics in the search option.
- Click on Google Analytics API in the listed options.
- Click on ENABLEand return to the previous page.
- Take Google Analytics Reporting APIlisted in the search options.
- Click on ENABLEand return to the main page.
- Click the OAuth consent screen.
- Create a new Internal/External (if you use your personal account, select External.
- Select Add Scope.
- Search for ../auth/analytics.readonly and check the same as Scopes for Google APIs.
- Select Save.
- Select Credentials.
- Add OAuth client ID credentials.
- Select Web application from the list in Create OAuth.
- Enter https://console.aws.amazon.com as an authorized origins URL.
- Use this https://AWSREGION.console.aws.amazon.com/appflow/oauth as an authorized redirect URL.
- Select Save.
Step 4: Set up Lambda and Amazon S3. Creating a new S3 bucket as an Amazon AppFlow transfer destination.
Select Create a Bucket and follow the necessary steps.
Step 5: Set up Amazon AppFlow. Create a new Amazon AppFlow to transfer from Google Analytics to Amazon S3.
For the Source name, select Google Analytics.
- Select Create a new connection.
- Enter your OAuth client ID and client secret, then name your connection
- In the pop-up window, select allow amazon.com access to the Google Analytics API.
- Select Reports as a Google Analytics object. Select All Web Site Data for Google Analytics view. Destination name, select Amazon S3.
- For Bucket details, select the bucket you created.
- Select Run on demand.
- Select Next.
Step 6: Select Manually map fields and source field names as the required fields. Select Map fields directly. Select Next. In the Add Filters section, select Next.
Select Run flow.
- Check the bucket for the output
Transferred data
Conclusion
Amazon AppFlow is a powerful and easy-to-use integration service that allows you to transfer data between SaaS applications and AWS services securely. With AppFlow, you can automate data transfers without writing any code and use pre-built connectors for popular SaaS applications. AppFlow also offers security, compliance, flexibility, and cost savings, making it an attractive choice for businesses looking to streamline their data transfer processes.
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About CloudThat
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Drop a query if you have any questions regarding Amazon AppFlow and I will get back to you quickly.
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FAQs
1. What are the available trigger mechanisms available for flows?
ANS: – On-demand, event-based, and scheduled trigger mechanisms are available for flows.
2. What kind of AWS services are supported by Amazon AppFlow?
ANS: – Amazon Connector Customer Profiles, Amazon Lookout for Metrics, Amazon S3, Amazon RedShift, and Amazon Honeycode.
WRITTEN BY Suresh Kumar Reddy
Yerraballi Suresh Kumar Reddy is working as a Research Associate - Data and AI/ML at CloudThat. He is a self-motivated and hard-working Cloud Data Science aspirant who is adept at using analytical tools for analyzing and extracting meaningful insights from data.
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