AWS Data Solutions and Orchestration

Podcast Beta

Play an AI-generated podcast conversation about this lesson

Questions and Answers

Which AWS service should be used to identify and obfuscate personally identifiable information (PII) in a data pipeline?

Detect PII transform in AWS Glue Studio (correct)

AWS Step Functions

Amazon EMR

AWS Lambda functions

What is the primary benefit of using AWS Step Functions in a data pipeline?

To perform data transformations

To store data securely

To orchestrate and automate workflows (correct)

To manage user access

In the context of a data pipeline, what is the purpose of Amazon S3?

To serve as the storage layer for data lakes (correct)

To monitor application performance

To act as a relational database

To execute serverless functions

Which solution would provide automated orchestration with minimal manual effort according to the requirements?

AWS Glue workflows Signup and view all the answers

Which AWS service would you use to ingest datasets into Amazon DynamoDB?

AWS Lambda functions Signup and view all the answers

What does the AWS Glue Data Quality rule accomplish in a data processing scenario?

It obfuscates PII data Signup and view all the answers

Which service allows for the creation of complex workflows that can include multiple AWS services?

AWS Step Functions Signup and view all the answers

When implementing an ETL pipeline that minimizes operational overhead, which service provides the best automation capabilities?

AWS Step Functions Signup and view all the answers

Which AWS service is the most cost-effective option for orchestrating an ETL data pipeline to crawl a Microsoft SQL Server table and load the output to an Amazon S3 bucket?

AWS Glue workflows Signup and view all the answers

What is the best solution for running real-time queries on Amazon Redshift from within a web-based trading application while minimizing operational overhead?

Use the Amazon Redshift Data API Signup and view all the answers

Which feature of AWS Glue is specifically designed to coordinate different ETL jobs and processes?

Glue workflows Signup and view all the answers

In what scenario would AWS Step Functions be more appropriate than AWS Glue workflows for managing data pipelines?

For workflows requiring integration with multiple AWS services Signup and view all the answers

When using the Amazon Redshift Data API, which advantage does it provide for querying data?

It provides a serverless architecture for data queries Signup and view all the answers

Which option is NOT a typical benefit of using AWS Glue for ETL processes?

Direct support for streaming data Signup and view all the answers

What is a key advantage of using Amazon S3 Select in conjunction with frequently accessed data?

It reduces the amount of data returned by queries, lowering costs. Signup and view all the answers

For a web-based trading application, what is a disadvantage of using traditional JDBC connections to Amazon Redshift compared to other methods?

Greater operational overhead in managing connections Signup and view all the answers

Which option best minimizes operational overhead for deduplicating legacy application data?

Write an AWS Glue ETL job using the FindMatches ML transform. Signup and view all the answers

What is a primary advantage of using AWS Glue for data deduplication over custom ETL solutions?

AWS Glue automatically scales based on data volume without user intervention. Signup and view all the answers

When migrating a legacy application with duplicate data, which method is least suitable for ensuring data integrity?

Ignoring duplicates and proceeding with data ingestion into the data lake. Signup and view all the answers

Which solution requires coding but still offers a robust approach to data deduplication?

Using the dedupe library within a custom ETL pipeline. Signup and view all the answers

What is the main drawback of using the Pandas library for data deduplication in large datasets?

It cannot handle data larger than memory limits. Signup and view all the answers

Which of the following is a feature of the AWS Glue ETL job when performing data deduplication?

It provides a fully managed environment for running ETL jobs. Signup and view all the answers

Which option represents a more complex transformation process compared to using AWS Glue?

Writing a custom ETL job using the dedupe library in Python. Signup and view all the answers

Which solution may necessitate the highest level of ongoing maintenance?

Employing the dedupe library in a custom Python ETL job. Signup and view all the answers

Which solution provides the least operational overhead for analyzing data in Amazon Kinesis Data Streams with multiple types of aggregations?

Use Amazon Managed Service for Apache Flink to perform time-based analytics. Signup and view all the answers

What is a key requirement for using AWS Lambda functions in time-based aggregations on Kinesis Data Streams?

They should include both business and analytics logic. Signup and view all the answers

Which migration method for upgrading from gp2 to gp3 Amazon EBS volumes minimizes the risk of data loss during the process?

Create snapshots of gp2 volumes and create new gp3 volumes from them. Signup and view all the answers

What is a disadvantage of gradually transferring data to new gp3 volumes during the upgrade from gp2?

It can cause data inconsistencies during the transfer. Signup and view all the answers

What is a key feature of Amazon Managed Service for Apache Flink regarding data analytics?

It allows for real-time data streaming analytics with low overhead. Signup and view all the answers

Which method would NOT be appropriate for ensuring continuous availability of EC2 instances during EBS volume upgrades?

Change the volume from gp2 to gp3 directly. Signup and view all the answers

Why might a Lambda function not be the best choice for conducting time-based aggregations over Kinesis Data Streams?

They can introduce high operational overhead compared to other solutions. Signup and view all the answers

What is the primary advantage of using Amazon Managed Service for Apache Flink for data analysis?

It performs analysis with minimal configuration and overhead. Signup and view all the answers

What is the most efficient way to query only one column from Apache Parquet format data in Amazon S3 with minimal overhead?

Use S3 Select to write a SQL SELECT statement on the S3 objects. Signup and view all the answers

Which method will require the least effort to automate refresh schedules for Amazon Redshift materialized views?

Use Apache Airflow to manage the refresh schedules. Signup and view all the answers

What kind of query can be executed using S3 Select?

SQL SELECT statements to retrieve specific columns from S3 objects. Signup and view all the answers

Which approach is not ideal for refreshing Amazon Redshift materialized views with low operational effort?

Manually refreshing views using the query editor v2. Signup and view all the answers

In the context of querying S3 data, what advantage does using S3 Select provide?

It results in faster query execution by reducing the amount of data processed. Signup and view all the answers

Which of the following is a disadvantage of using AWS Lambda for data processing tasks?

There may be cold start latency affecting performance. Signup and view all the answers

What is a potential drawback of preparing an AWS Glue DataBrew project for querying S3 data?

It requires more setup time compared to direct querying via S3 Select. Signup and view all the answers

Which solution is least advisable for maintaining Amazon Redshift materialized views?

Manual intervention for each refresh. Signup and view all the answers

Which solution will meet the requirements with the least management overhead for orchestrating a data pipeline that consists of one AWS Lambda function and one AWS Glue job?

Use an AWS Step Functions workflow that includes a state machine. Configure the state machine to run the Lambda function and then the AWS Glue job. Signup and view all the answers

Study Notes

AWS Glue Workflows and Data Orchestration

AWS Glue Workflows are the most cost-effective way to orchestrate an ETL data pipeline that crawls data from Microsoft SQL Server, performs ETL, and loads data into an Amazon S3 bucket.

Real-Time Queries on Amazon Redshift

Amazon Redshift Data API is the solution with the least operational overhead to run real-time queries from a web-based trading application that accesses financial data stored in Amazon Redshift.

Automated Orchestration for ETL Workflows

AWS Step Functions are the solution with the least operational overhead to provide automated orchestration for ETL workflows that ingest data from operational databases to an Amazon S3-based data lake, using AWS Glue and Amazon EMR.

Data Deduplication in Legacy Application Migrations

AWS Glue ETL job with FindMatches machine learning transform is the solution with the least operational overhead to identify and remove duplicate information from legacy application data being migrated to an Amazon S3-based data lake.

Time-Based Analytics in Analytics Solutions

Amazon Managed Service for Apache Flink is the solution with the least operational overhead to analyze data that might contain duplicates, including time-based analytics over a window of up to 30 minutes, using multiple types of aggregations, in an analytics solution using Amazon S3 for data storage and Amazon Redshift for a data warehouse.

Upgrading Amazon EBS Storage

Create new GP3 volumes, transfer data gradually, and replace existing GP2 volumes is the solution with the least operational overhead to prevent interruptions in EC2 instances during migration to upgraded storage.

Reading Data from S3 Objects

Using S3 Select with a SQL SELECT statement is the solution with the least operational overhead to read data from S3 objects in Apache Parquet format and query only one column.

Automating Redshift Materialized View Refresh

Using Apache Airflow is the solution with the least effort to automate refresh schedules for Amazon Redshift materialized views.

Data Pipeline Orchestration

Requirement: Orchestrate a data pipeline with AWS Lambda and AWS Glue job.
Goal: Minimize management overhead.
Solution: AWS Step Functions workflow.
Steps:
- Define a state machine.
- Configure the state machine to execute Lambda function first.
- Then, execute AWS Glue job.
This approach offers the least management overhead by leveraging a fully managed service (AWS Step Functions) and simplifying the workflow definition.

Studying That Suits You

Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

Description

This quiz covers key concepts related to AWS Glue workflows, Amazon Redshift, and automated ETL orchestration using AWS Step Functions. Explore how these services can be applied in real-time querying and data deduplication strategies. Test your knowledge on the most cost-effective solutions for data management in AWS.