Amazon Redshift Materialized Views Quiz

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Questions and Answers

Which solution will make the data available for the data visualizations with the LEAST latency?

Use Amazon Athena to query the data from the Avro objects in Amazon S3. Configure Amazon Keyspaces as the data catalog. Connect Amazon QuickSight to Athena to create the dashboards.

Use AWS Glue to catalog the data. Use S3 Select to query the Avro objects in Amazon S3. Connect Amazon QuickSight to the S3 bucket to create the dashboards.

Use Amazon Athena with an Apache Hive metastore to query the Avro objects in Amazon S3. Use Amazon Managed Grafana to connect to Athena and to create the dashboards.

Create OpenSearch Dashboards by using the data from OpenSearch Service. (correct)

Which command will reclaim the MOST database storage space from a materialized view in Amazon Redshift?

VACUUM table_name where load_date

TRUNCATE materialized_view_name (correct)

DELETE FROM materialized_view_name where 1=1

Which solution will meet the requirements of converting .csv files to JSON format and storing them in Apache Parquet format with the least development effort?

Use Kinesis Data Firehose to convert the .csv files to JSON. Use an AWS Lambda function to store the files in Parquet format.

Use Kinesis Data Firehose to invoke an AWS Lambda function that transforms the .csv files to JSON and stores the files in Parquet format.

Use Kinesis Data Firehose to invoke an AWS Lambda function that transforms the .csv files to JSON. Use Kinesis Data Firehose to store the files in Parquet format.

Use Kinesis Data Firehose to convert the .csv files to JSON and to store the files in Parquet format. (correct)

Which solution will meet the company policy requirement to use TLS 1.2 or above for data in transit during migration?

Update the security policy of the Transfer Family server to specify a minimum protocol version of TLS 1.2. Signup and view all the answers

Which solution will meet the requirements of migrating an application and an on-premises Apache Kafka server with the least management overhead?

Amazon Managed Streaming for Apache Kafka (Amazon MSK) Serverless Signup and view all the answers

Which AWS Glue feature should the data engineer use to support incremental data processing?

Job bookmarks Signup and view all the answers

What solution will help ensure exactly-once delivery in the processing pipeline for Kinesis Data Streams?

Design the application to remove duplicates during processing by embedding a unique ID in each record at the source. Signup and view all the answers

Which solution will prevent unintentional file deletion in an Amazon S3 bucket?

Enable S3 Versioning for the S3 bucket. Signup and view all the answers

What solution will help detect drops in network usage with the least latency for a telecommunications company?

Modify the processing application to publish the data to an Amazon Kinesis data stream. Create an Amazon Managed Service for Apache Flink application to detect drops in network usage. Signup and view all the answers

What solution will give data analysts the ability to perform complex queries with the least operational overhead when using Amazon Redshift?

Use AWS Glue DataBrew to prepare the data. Use AWS Glue to load the data into Amazon Redshift. Use Amazon Redshift to run queries. Signup and view all the answers

Which solution will ensure the AWS Glue crawler creates only one table from the processed S3 bucket objects?

Ensure that the object format, compression type, and schema are the same for each object. Signup and view all the answers

Which solutions will minimize data loss for an application consuming messages from an Amazon SQS queue?

Attach a dead-letter queue (DLQ) to the SQS queue. Signup and view all the answers

Which solution will most cost-effectively allow a data engineer to automatically run an Amazon Redshift stored procedure on a daily basis?

Use query editor v2 to run the stored procedure on a schedule. Signup and view all the answers

Which combination of steps will meet the requirements for a marketing company to build dashboards with daily updates about clickstream activity in the most cost-effective way? (Choose two.)

Access the query data through QuickSight SPICE (Super-fast, Parallel, In-memory Calculation Engine) and configure a daily refresh for the dataset. Signup and view all the answers

Which service should a data engineer use to prioritize portability and open-source resources in both on-premises and cloud-based environments?

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) Signup and view all the answers

Which fully managed AWS solution will handle high online transaction processing (OLTP) workload with the least operational overhead?

Amazon DynamoDB Signup and view all the answers

How should a data engineer resolve an AccessDeniedException when invoking an AWS Lambda function via an EventBridge event?

Ensure that both the IAM role that EventBridge uses and the Lambda function's resource-based policy have the necessary permissions. Signup and view all the answers

Which solution allows a company to apply dual-layer server-side encryption to files uploaded to an S3 bucket?

Use dual-layer server-side encryption with AWS KMS keys (DSSE-KMS). Signup and view all the answers

What can a data engineer do to prevent Amazon Athena queries from queuing?

Configure provisioned capacity for an existing workgroup. Signup and view all the answers

What is likely the reason an AWS Glue job reprocesses files that were loaded during previous runs?

The AWS Glue job does not have the s3:GetObjectAcl permission required for bookmarks to work correctly. Signup and view all the answers

Which solution meets the requirements for a company migrating data pipelines from an on-premises environment to AWS with the least operational overhead?

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) Signup and view all the answers

Which solution meets the requirements for gathering near real-time insights from a product lifecycle management application using an on-premises MySQL database?

Run a full load plus CDC task in AWS Database Migration Service (AWS DMS) to continuously replicate MySQL database changes. Signup and view all the answers

What is the most cost-effective serverless solution for a company needing to query clickstream data stored in Amazon S3 while maintaining ACID properties?

Amazon Athena Signup and view all the answers

What setup will give AWS Database Migration Service (AWS DMS) the ability to replicate data between two data stores in different AWS regions?

Set up an AWS DMS replication instance in Account_B in eu-west-1. Signup and view all the answers

What solution can speed up data ingestion into Amazon Redshift without increasing costs?

Create a manifest file with data file locations and use a COPY command to load into Redshift. Signup and view all the answers

Study Notes

Scheduling Stored Procedures

Scenario: A data engineer needs to automatically run a non-critical Redshift stored procedure daily.
Solution: Use Query Editor v2 for scheduling the stored procedure.
Why: This is the most cost-effective option.

Clickstream Dashboarding

Scenario: A company wants to create dashboards for clickstream data stored in S3, accessible by multiple users, scaling daily.
Solution: Combine Amazon Athena and Amazon QuickSight with daily refreshes.
Why: This combination allows for queries to access data and provides a cost-effective solution for the scaling needs.

Data Orchestration

Scenario: A data engineer working with a hybrid environment (on-premises and cloud) seeks a portable, open-source solution for data orchestration.
Solution: Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA).
Why: It meets the requirements for portability and open-source resources while working across the on-premises and cloud-based environments.

NoSQL Database Migration

Scenario: A company migrating a NoSQL database to AWS needs a managed solution that can handle high transaction volume, deliver fast performance, and provide global availability.
Solution: Choose Amazon DynamoDB.
Why: It minimizes operational overhead while meeting the company’s performance and availability requirements.

AccessDeniedException Resolution in EventBridge

Scenario: A data engineer encounters an AccessDeniedException when invoking a Lambda function through an EventBridge event.
Solution: Ensure that both the IAM role used by EventBridge and the Lambda function's resource-based policy have the necessary permissions.
Why: Both the EventBridge role and the Lambda function's policy need to be configured to allow the interaction between the services for the invocation to function correctly.

Dual-Layer Encryption for Data Lake

Scenario: A company wants to meet regulatory requirements by applying two layers of encryption to data files uploaded to an S3 data lake.
Solution: Utilize dual-layer server-side encryption with AWS KMS keys (DSSE-KMS) for the S3 bucket.
Why: DSSE-KMS provides the necessary two layers of encryption to meet regulatory compliance.

Preventing Athena Query Queuing

Scenario: A data engineer observes Athena queries being queued.
Solution: Configure provisioned capacity for the appropriate workgroup.
Why: Allocating a dedicated capacity for the workgroup prevents queries from queuing and allows them to run smoothly.

Debugging AWS Glue Jobs

Scenario: A data engineer encounters an issue with an AWS Glue job that reads from S3 and writes to Redshift. The data engineer suspects an issue with bookmarking.
Solution: Ensure the AWS Glue job possesses the s3:GetObjectAcl permission required for bookmarking to work correctly.
Why: Without the s3:GetObjectAcl permission, bookmarking will not function properly, resulting in the job potentially reprocessing files.

Data Pipeline Migration from On- Premises

Scenario: An ecommerce company wants to migrate data pipelines from on-premises to AWS without server management and refactorization, and needs to support both Python and Bash scripting.
Solution: Implement Amazon Managed Workflows for Apache Airflow (Amazon MWAA).
Why: It offers a serverless solution for orchestrating data ingestion processes, supporting Python and Bash scripting, and simplifying the migration.

Near Real-Time Data Integration with Redshift

Scenario: A retail company needs to integrate data from an on-premises MySQL database, updated frequently by transactions, with their Redshift data warehouse in near real-time.
Solution: Use AWS Database Migration Service (AWS DMS) with a full load plus CDC (Change Data Capture) task to replicate data from the MySQL database to Redshift continuously.
Why: AWS DMS provides a simple and efficient method for continuously replicating database changes, minimizing development effort.

Serverless Querying on Clickstream Data in S3

Scenario: A marketing company stores clickstream data in S3 and needs a serverless solution to allow users to query data based on partitions while maintaining ACID properties.
Solution: Use Amazon Athena.
Why: Athena provides a serverless query engine for S3 data offering ACID properties.
Alternative: Amazon Redshift Spectrum could be an alternative, but may not be as cost-effective for this specific scenario.

Replicating Data Between AWS Accounts

Scenario: A company needs to migrate data from a PostgreSQL DB instance in one AWS account to a Redshift cluster in a different AWS account.
Solution: Set up an AWS DMS replication instance in the target account (Account_B) in the target region (eu-west-1).
Why: AWS DMS allows for data replication across AWS accounts and regions.

Optimizing Data Ingestion into Redshift

Scenario: A company wants to increase the speed of data ingestion into a Redshift cluster from an S3 data lake while maintaining cost-effectiveness.
Solution: Create a manifest file containing the locations of the data files and use a COPY command to load the data into Redshift.
Why: Using a manifest file enables parallel loading of the data files into Redshift, resulting in significantly faster data ingestion.

Converting CSV Data to Parquet Format with Kinesis

Scenario: A company using Kinesis Data Firehose wants to convert CSV data to JSON format and then store it in Apache Parquet format in S3.
Solution: Configure Kinesis Data Firehose to convert CSV to JSON and store files in Parquet format.
Why: Kinesis Data Firehose allows for direct conversion and storage in the desired format, minimizing development effort.

TLS 1.2 or Above Encryption with AWS Transfer Family

Scenario: A company using AWS Transfer Family for migrating data from on-premises to AWS needs to ensure data is encrypted in transit using TLS 1.2 or above.
Solution: Update security group rules for the on-premises network to allow connections using only TLS 1.2 or above.
Why: By configuring network-level encryption using TLS 1.2, the company can ensure the data transfer is secured according to their policy.

Security Policy Update

Updating security policy to specify TLS 1.2 minimum protocol version is necessary to ensure secure data transfers.
Installing an SSL certificate on the server enables TLS 1.2 encryption for data transfers

Migrating to AWS

Replatforming an application and an on-premises Apache Kafka server to AWS, with the least management overhead, can be achieved using Amazon MSK Serverless.
It offers a fully managed serverless option for Apache Kafka, reducing operational burden for the user.

ETL Pipeline with Incremental Data Processing

AWS Glue Job Bookmarks enable incremental data processing in an automated ETL ingestion pipeline by storing the last processed record's location.
This allows the pipeline to efficiently process only new or updated data files, saving time and resources.

Exactly-Once Delivery in Kinesis Data Streams

Embedding a unique ID in each record at the source allows for duplicate removal during processing, ensuring exactly-once delivery in Kinesis Data Streams.
This eliminates the potential for data duplication and maintains data integrity in the processing pipeline.

Preventing Unintentional File Deletion in S3

Enabling S3 Versioning for the S3 bucket provides a mechanism to prevent unintentional file deletion.
It keeps track of all changes to objects in the bucket, creating a version history, allowing recovery from accidental deletions.

Identifying Sudden Drops in Network Usage

Modify the processing application to publish data to an Amazon Kinesis data stream, and utilize an Amazon Managed Service for Apache Flink application to detect network usage drops.
This approach provides real-time monitoring and analysis, allowing for immediate identification of network outages for quicker remedial actions.

Data Preparation and Loading into Amazon Redshift

Using AWS Glue DataBrew for data preparation and AWS Glue for loading data into Amazon Redshift provides a streamlined, operationally efficient solution.
It eliminates the need for complex ETL processes and infrastructure management, making the process manageable and scalable.

Securely Transferring Files from SFTP to S3

Creating a VPC gateway endpoint for Amazon S3 within the VPC, ensures secure communication between the Lambda function and S3, resolving timeout errors.
It provides a secure and cost-effective solution for data transfer without exposing the Lambda function to the public internet.

Data Integration Across Databases with Inconsistent Fields

Creating an AWS Glue crawler to scan the databases utilizes the FindMatches transform to identify duplicate records effectively.
It eliminates the need for complex data processing and ensures efficient linking of customer records across different databases by finding duplicates.

Ensuring Consistent Data Catalog Creation

Both consistent object format, compression type, and schema, along with a consistent structure for S3 object name prefixes are required for only one table creation in the AWS Glue crawler.
This ensures the crawler accurately interprets the data and creates a unified table in the data catalog, minimizing confusion.

Minimizing Data Loss in Amazon SQS Queue

Two solutions mitigate data loss in Amazon SQS: increasing the message retention period and attaching a dead-letter queue (DLQ) to the queue.
Increasing the retention period prevents messages from expiring too quickly, while the DLQ allows failed messages to be stored for troubleshooting, reducing the impact of application downtime.

Creating Real-Time Dashboards with Low Latency

Create OpenSearch Dashboards by using the data from OpenSearch Service.
It offers minimal latency, enabling near real-time visualizations for time series data stored in OpenSearch Service, making it ideal for timely insights.

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Description

This quiz tests your knowledge on optimizing data availability and storage in Amazon Redshift. Focus on queries and commands that minimize latency and reclaim storage efficiently. Sharpen your skills in managing materialized views for better performance.