How to create a query in Dataslayer for Amazon S3

In this article, we will explain everything you need to know to create a query in AWS S3 with Dataslayer. Just follow these simple steps.

1.  Log in to our website.

2.  Click on Open under the Amazon S3 Destination.

3.  You will see the index of your queries, click on New Transfer.

1.  Select the email you want to connect with.

• If you are already logged in to the Hub, select the email and click Confirm.
• If you are not logged in, click Manage Hub Accounts and follow the steps to add a new account.

2.  Select the data you want to include in your query.

• You will need to select a date range.
• The metrics and dimensions you want to add.
• Filters and options if needed.

Save as a Template

1.  Select the S3 bucket you want to connect with.

• If you are already logged in to a bucket, select the link on the drop-down and click Transfer Data.
• If you are not logged in, click on Connect with AWS and follow the steps to add a new bucket.

2. Fill in all the fields.

• Transfer Name: This will be the name of the transfer in Dataslayer. This name is only visible to you and is not transferred to AWS.
• Time zone: Select your time zone.
• File Name: This is the name of the file we are creating with the data. This name is visible on AWS.
• Upload Path: This field is optional and is the folder path, you can set several folders separated by "/". If the entered folder does not exist it will be created in S3.
  Example: If you set File Name "file.csv" and Upload path "a/b" it will dump it inside S3 in a/b/file.csv
• Write mode: Select the write mode you want.

3. Select the Sync Frequency of your transfer.

4. Done! Finally, save your transfer.

• Click on Save to only save your transfer in Dataslayer. 
• Click on Save & Refresh Now to save the transfer and insert the data on S3. 

 

Preview

If you want to see what the table you have created will look like, you can click on the Preview button to see it.

This way you can make modifications, if you have detected any errors or if you want to change the order of the columns, before uploading the table into AWS.

Preview

As always, please do not hesitate to contact us via our live chat on our website or via e-mail if you still have doubts or questions. We are happy to help!