Class 9. Data Manipulation

What is the purpose of a data lake?

• To store data in a structured and cleaned format only

• To collect and store massive amounts of structured and unstructured data from any number of places

• To duplicate data for backup purposes

• To perform online transaction processing

Which AWS service allows you to create a data lake?

• AWS Transfer Family

• AWS Data Firehose

• AWS Lake Formation

• AWS Glue

What operations can AWS Glue perform?

• Online Analytical Processing (OLAP) only

• Extract, Transform, Load (ETL) operations

• Data deduplication

• Data visualization

Can a data lake store all your data as is, without the need for structuring or cleaning?

• No, it must be structured and cleaned

• Yes, but it must be deduplicated

• Yes, it can store all your data as is

• No, it can only store structured data

What is AWS Glue based on?

• The AWS proprietary framework

• The Apache Spark big data framework

• The Hadoop ecosystem

• The AWS Kinesis framework

What is the process of collecting data from various sources and pulling it into your data lake known as?

• Transformation

• Analytics

• Ingestion

• Cataloging

Which AWS service is NOT mentioned as a source from which AWS Lake Formation can import data?

• AWS Glue

• AWS CloudFront

• AWS CloudTrail

• AWS S3

What does AWS Glue Data Catalog store?

• Data lake configuration settings

• Metadata about the data lake

• Physical data files

• User access logs

What is the purpose of the FindMatches ML transform in AWS Lake Formation?

• To classify data according to sensitivity

• To visualize data patterns

• To deduplicate data

• To import data from on-premises databases

Which of the following is NOT a function of analytics as described in the text?

• Querying data

• Visualizing data

• Deduplicating data

• Performing statistical functions on data