DEA-C01 Question 214
Select 3You are working as a data engineer for a company that uses AWS Glue Data Catalog to manage metadata for their data lake. The team wants to ensure that the catalog is well-structured and provides meaningful insights into the stored datasets. Which components of the AWS Glue Data Catalog should you focus on to achieve this?
- A
Tables that define the schema and structure of datasets
- B
Crawlers to automate the creation of metadata entries
- C
Triggers to start data workflows based on conditions
- D
Database objects to logically organize tables
- E
Job definitions for transforming data
Show answer and explanation
Correct answers: A, B, D
Explanation
To structure and manage an AWS Glue Data Catalog effectively, you need to focus on components such as tables, crawlers, and databases. Tables define the schema and structure of datasets, crawlers automate metadata discovery and updating, and databases help organize tables logically. Triggers and job definitions, while useful in data workflows, are not directly related to catalog metadata management.
- A. Correct.
Tables are essential components of the AWS Glue Data Catalog. They store schema information, including column names, data types, and locations of datasets, which helps define the structure of data.
- B. Correct.
Crawlers are used to automate the discovery and creation of metadata entries in the catalog by scanning datasets. This ensures that the metadata stays up-to-date and well-organized.
- C. Incorrect.
Triggers are part of AWS Glue workflows but are not directly related to managing or structuring metadata in the Data Catalog.
- D. Correct.
Databases in the AWS Glue Data Catalog are used to logically group and organize tables, helping to maintain a structured catalog.
- E. Incorrect.
Job definitions in AWS Glue are used for ETL (Extract, Transform, Load) processes and do not directly contribute to the structure or management of the metadata catalog.