![]() ![]() ![]() On the next screen, select PowerUserAccess as the policy and click on the Next: Tags button. On the next screen, select Redshift - Customizable as the service \ use case and click on the Next: Permissions button. Goto the IAM Management console and click on the Roles menu in the left and then click on the Create role button. You create IAM Role for the Redshift cluster which is used to provide access to the data in the S3 bucket. The next step is to create IAM Role for the Redshift cluster. You will access this data from Redshift cluster using Redshift Spectrum. It has dummy data of countries and their business index. The sampledata.csv file looks like below. Upload sampledata.csv file to the bucket. If the bucket name is not available, create bucket with a name which is available. ![]() Login to the AWS Console and choose Ireland as the region. Step2: Create S3 BucketĪ sample data file ( sampledata.csv) has been provided for the exercise. If you don’t have an AWS account, kindly use the link to create free trial account for AWS. You need to have an AWS account with administrative access to complete the exercise. The AWS Resource consumption for the exercise does not fall under AWS Free Tier. In this exercise, you learn how to use Amazon Redshift Spectrum to access S3 based data from Amazon Redshift. Amazon Redshift enables S3 data access from Amazon Redshift. The user can access the S3 data from Redshift in the same way, the data is accessed from the Redshift storage itself. It enable a very cost effective data warehouse solution where the warm data can be kept in Amazon Redshift storage while the cold data can be kept in the S3 storage. Amazon Redshift provides seamless integration with other storages like Amazon S3. It is recommended to clean-up the resources as soon as you finish the exercise to minimize the cost.Īccess S3 Data in Amazon Redshift using Redshift SpectrumĪmazon Redshift is the cloud data warehouse in AWS. Important Note: You will create AWS resources during the exercise which will incur cost in your AWS account. ![]()
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