DEA-C01 Question 211
Select 3You are designing a data lake architecture on AWS and need to ensure that datasets are discoverable and searchable by analysts across your organization. Which components of a metadata and data catalog are essential to achieve this requirement?
- A
Schema definitions for datasets
- B
Data access policies and permissions
- C
Data lineage tracking
- D
Integration with query engines like Amazon Athena
- E
Real-time data replication
Show answer and explanation
Correct answers: A, C, D
Explanation
To make datasets discoverable and searchable, a metadata and data catalog must provide schema definitions, data lineage, and integration with query tools. Schema definitions help users understand the structure of data, data lineage ensures traceability, and integration with query tools enables seamless data querying. While data access policies and real-time replication are important in a broader data system, they are not core components of a metadata and data catalog.
- A. Correct.
Schema definitions for datasets are a critical part of metadata as they provide information about the structure and organization of data, making it easier for analysts to understand and query the datasets.
- B. Incorrect.
Data access policies and permissions, while important for security, are not a primary component of a metadata or data catalog. They are more related to access control mechanisms.
- C. Correct.
Data lineage tracking is an essential component of a metadata and data catalog as it helps track the origin, transformations, and dependencies of datasets, which is crucial for trust and traceability.
- D. Correct.
Integration with query engines like Amazon Athena allows analysts to directly query datasets from the catalog, enhancing data discoverability and usability.
- E. Incorrect.
Real-time data replication is a data processing or availability feature, not a component of a metadata or data catalog.