Amazon Web Services DAS-C01 Dumps Questions Answers

This solution meets the requirements because:

• AWS Glue is a fully managed extract, transform, and load (ETL) service that can be used to prepare and load data for analytics1. You can use AWS Glue to create a job that copies the CloudTrail logs from the source S3 bucket to a new S3 bucket, and converts them to Apache Parquet format2. Parquet is a columnar storage format that is optimized for analytics and supports compression3. Snappy is a compression codec that provides a good balance between compression ratio and speed4.
• AWS Glue can also create a table based on the Parquet files in the new S3 bucket, and partition the table by date2. Partitioning is a technique that divides a large dataset into smaller subsets based on a partition key, such as date5. Partitioning can improve query performance by reducing the amount of data scanned and filtering out irrelevant data5.
• Amazon Athena is an interactive query service that allows you to analyze data in S3 using standard SQL6. You can use Athena to query the table created by AWS Glue, and specify the partitions you want to query based on the daterange. Athena can leverage the benefits of Parquet format and partitioning to run queries faster and more cost-effectively.

This solution meets the requirements because:

• AWS Step Functions is a fully managed service that allows you to create and orchestrate workflows that connect various AWS services, such as AWS Glue, Amazon EMR, Amazon S3, and others1. You can use Step Functions to automate your data workflows and handle complex logic, such as branching, parallel processing, error handling, retries, and timeouts1.
• AWS Step Functions provides a graphical interface that lets you design and visualize your workflows as state machines, which are composed of a series of steps or tasks1. You can use the AWS Step Functions console, the AWS CLI, or the AWS SDKs to create and manage your state machines1.
• AWS Step Functions integrates with AWS Glue and Amazon EMR to enable you to run data processing and ETL jobs as part of your workflows23. You can use the built-in connectors for these services to invoke them from your state machines23. You can also use Step Functions to monitor the status of your jobs and trigger actions based on the job outcomes23.
• AWS Step Functions can help you minimize manual intervention by providing features such as automatic retries, catch blocks, and fallback states, which allow you to handle errors and failures gracefully in your workflows1. You can also use Step Functions to trigger your workflows based on events, such as a new file in S3 or a CloudWatch alarm1.