Once you get everything working with a single file, you can parameterize your API and Lambda function to accept an s3 path so that you can pull in anything from your S3 account.

and tell the csv parser the delimiter and encodingīinary = Binary.Decompress(raw, Compression.GZip), My file is a gzipped utf-8 tsv, so I need to decompress it Make sure to set IsRetry to true so that PowerBI gets a fresh url with a PowerBI should understand the 303 redirect and follow it to your presigned s3 url Replace the URI with the 'invoke url' of your API Gateway endpoint You can use this PowerBI query as a starting point: let Here is a sample of a lambda function in python 2.7: bucket = 'bucket-name'

4.2 Return a 303 redirect to the url from step 4.1.

4.1 Using the AWS SDK, generate a url w/ pre-signed key for your file.3.3 Select the region and type in the name of the lambda function you created in step 1.3.2 Select the Use Lambda Proxy integration option.3.1 Select Lambda Function for the integration type.Here is the relevant answer from the user spinwards: The use case that I have is that the individual that is going to be using this PowerBI template wants to log in and be done with authentication from that point.Īnother option for accessing an S3 bucket through PowerBI is to use AWS API Gateway and Lambda functions to create a pre-signed URL, as per this question on the Power BI forums. Your accepted answer is great as long as whoever is using the PowerBI query has the AWS CLI on their machine.

Cyberduck connect to s3