DVA-C02: How to Use AWS Services for Scalable Data Management and Orchestration

Learn how to build a scalable data management solution using AWS services that can ingest, process, and orchestrate large volumes of data from various sources. Find out which AWS service is best suited for managing and automating the data flows with minimal maintenance.

Question

A company is building a scalable data management solution by using AWS services to improve the speed and agility of development. The solution will ingest large volumes of data from various sources and will process this data through multiple business rules and transformations.

The solution requires business rules to run in sequence and to handle reprocessing of data if errors occur when the business rules run. The company needs the solution to be scalable and to require the least possible maintenance.

Which AWS service should the company use to manage and automate the orchestration of the data flows to meet these requirements?

A. AWS Batch
B. AWS Step Functions
C. AWS Glue
D. AWS Lambda

Answer

B. AWS Step Functions

Explanation

The correct answer is B. AWS Step Functions.

Here is a detailed explanation:

• Option A is not a valid solution because AWS Batch is not designed for orchestrating data flows. AWS Batch is a service that enables users to run batch jobs on AWS, such as processing large data sets, running simulations, or performing machine learning inference. However, AWS Batch does not provide features for managing and automating the sequence and logic of the data flows, such as handling errors, retries, branching, and parallelism.
• Option B is the best solution because AWS Step Functions is a service that provides scalable and reliable orchestration of data flows. AWS Step Functions allows users to create state machines that define the steps and transitions of the data flows using a JSON-based language. AWS Step Functions also integrates with other AWS services, such as AWS Lambda, Amazon S3, and Amazon DynamoDB, to perform various tasks on the data. Moreover, AWS Step Functions provides features for handling errors, retries, branching, parallelism, and monitoring of the data flows.
• Option C is not a valid solution because AWS Glue is not designed for orchestrating data flows. AWS Glue is a service that provides serverless data integration for analytics users. AWS Glue allows users to discover, prepare, move, and integrate data from multiple sources using the Glue Data Catalog and the Glue ETL engine. However, AWS Glue does not provide features for managing and automating the sequence and logic of the data flows, such as handling errors, retries, branching, and parallelism.
• Option D is not a valid solution because AWS Lambda is not designed for orchestrating data flows. AWS Lambda is a service that allows users to run code without provisioning or managing servers. AWS Lambda can be used to perform various tasks on the data, such as processing, transforming, or validating. However, AWS Lambda does not provide features for managing and automating the sequence and logic of the data flows, such as handling errors, retries, branching, and parallelism.

Therefore, option B is the best solution that meets these requirements.

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