Data Lake and Lake Formation
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Questions and Answers

What type of data can Amazon Redshift handle?

  • Only semi-structured data
  • Only structured data
  • Only unstructured data
  • Both structured and semi-structured data (correct)

    • Which of these is NOT a benefit of using Amazon Redshift Serverless?

  • Automatic provisioning and scaling of data warehouse capacity
  • Pay-as-you-go pricing model
  • Requires manual infrastructure management (correct)
  • Provides fast performance for demanding workloads

    • Which service allows you to process streaming data using Apache Kafka?

  • Amazon MSK (correct)
  • Amazon Redshift
  • Amazon Athena
  • Amazon QuickSight

    • What is the primary function of Amazon Redshift?

    <p>Storing and analyzing large datasets</p> Signup and view all the answers

    Which service can be used to analyze data stored in an Amazon S3 data lake?

    <p>All of the above</p> Signup and view all the answers

    What is the main advantage of using Amazon Redshift over traditional on-premises solutions?

    <p>Significantly lower costs</p> Signup and view all the answers

    What does Amazon Redshift use to achieve fast query completion?

    <p>Massively parallel query execution</p> Signup and view all the answers

    What is the primary function of Lake Formation?

    <p>To create and manage data lakes by automating various tasks.</p> Signup and view all the answers

    Which of the following is NOT a benefit of using a data lake?

    <p>Simplified data management with minimal automation</p> Signup and view all the answers

    Which of these is NOT a use case for Amazon Redshift Serverless?

    <p>Developing serverless functions</p> Signup and view all the answers

    What is the primary type of database management system used by Amazon Redshift?

    <p>Relational</p> Signup and view all the answers

    Which service enables interactive data analysis and querying of data stored in Amazon S3?

    <p>Amazon Athena</p> Signup and view all the answers

    How does Amazon Redshift Serverless ensure cost-effectiveness for users?

    <p>By charging only for the resources used</p> Signup and view all the answers

    Which service provides a fully managed data warehouse solution?

    <p>Amazon Redshift</p> Signup and view all the answers

    Which service can be used to build machine learning models using data stored in an Amazon S3 data lake?

    <p>SageMaker</p> Signup and view all the answers

    Which of the following is NOT a task typically involved in setting up and managing a data lake?

    <p>Setting up and managing relational database schemas</p> Signup and view all the answers

    What is one primary function of AWS Entity Resolution?

    <p>To remove duplicate records and create customer profiles</p> Signup and view all the answers

    What does AWS Glue primarily assist with?

    <p>Extracting, transforming, and loading data for analytics</p> Signup and view all the answers

    Which of the following engines does AWS Glue Data Integration provide access to?

    <p>Apache Spark, PySpark, and Python</p> Signup and view all the answers

    How does AWS Glue Data Quality help users?

    <p>By automatically detecting and monitoring data quality issues</p> Signup and view all the answers

    What is the primary purpose of AWS Lake Formation?

    <p>To help set up secure data lakes quickly</p> Signup and view all the answers

    In the context of AWS services, what does ETL stand for?

    <p>Extract, Transform, Load</p> Signup and view all the answers

    Which of the following describes the role of AWS Glue Data Catalog?

    <p>A repository of metadata that makes data easily searchable and queryable</p> Signup and view all the answers

    What common feature does AWS Glue offer for scaling workloads?

    <p>Integration with big data processing frameworks</p> Signup and view all the answers

    Study Notes

    Data Lake

    • A centralized, curated, and secured repository that stores all data, both in its original form and prepared for analysis.
    • Enables breaking down data silos and combining different types of analytics to gain insights and guide better business decisions.

    Lake Formation

    • Simplifies setting up and managing data lakes by defining data sources and applying access and security policies.
    • Collects and catalogs data from databases and object storage, moves data into Amazon S3, cleans and classifies data using ML algorithms, and secures access to sensitive data.
    • Provides a centralized catalog of data that describes available data sets and their usage.

    AWS Glue

    • A fully managed extract, transform, and load (ETL) service that prepares and loads data for analytics.
    • Discovers data, stores metadata in the AWS Glue Data Catalog, and makes data searchable, queryable, and available for ETL.
    • Provides access to data using Apache Spark, PySpark, and Python, and can scale workloads using Ray.

    AWS Glue Data Quality

    • Measures and monitors data quality of Amazon S3 based data lakes, data warehouses, and other data repositories.
    • Automatically computes statistics, recommends quality rules, and monitors and alerts when detecting missing, stale, or bad data.

    Amazon Redshift

    • A cloud data warehouse that makes it fast, simple, and cost-effective to analyze all data using standard SQL and existing Business Intelligence (BI) tools.
    • Allows running complex analytic queries against terabytes to petabytes of structured and semi-structured data.
    • Provides fast performance, scalable storage, and cost-effective pricing.

    Amazon Redshift Serverless

    • Makes it easier to run and scale analytics without managing data warehouse infrastructure.
    • Automatically provisions and scales data warehouse capacity to deliver fast performance for demanding workloads.
    • Provides flexible, familiar SQL features in an easy-to-use, zero administration environment.

    Amazon Managed Streaming for Apache Kafka (Amazon MSK)

    • A fully managed service that makes it easy to build and run applications that use Apache Kafka to process streaming data.

    AWS Entity Resolution

    • Uses flexible, configurable ML and rule-based techniques to remove duplicate records, create customer profiles, and personalize experiences across advertising and marketing campaigns.
    • Can create a unified view of customer interactions by linking recent events, such as ad clicks, cart abandonment, and purchases, into a unique match ID.

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    Related Documents

    AWS-services-overview.pdf

    Description

    Understand the concept of a data lake and how Lake Formation simplifies setting up and managing data lakes to gain business insights.

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