Databricks Certified Data Engineer - Associate
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Which of the following describes a benefit of a data lakehouse that is unavailable in a traditional data warehouse?
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UAnonymous
A
A data lakehouse provides a relational system of data management.
B
A data lakehouse captures snapshots of data for version control purposes.
C
A data lakehouse couples storage and compute for complete control.
D
A data lakehouse utilizes proprietary storage formats for data.
E
A data lakehouse enables both batch and streaming analytics.
Explanation:
The primary benefit highlighted is that a data lakehouse supports both batch and streaming analytics from the same storage system. Traditional data warehouses are typically designed for batch-oriented workloads and analytical queries on structured data, whereas a lakehouse (for example, Databricks Lakehouse with Delta Lake) unifies data warehousing and data lakes to support streaming ingest/processing and batch analytics together. While snapshot/versioning (time travel) is also a capability offered by some lakehouse implementations (Delta Lake provides time travel), the best single answer for a benefit broadly unavailable in traditional data warehouses is the unified support for both batch and streaming analytics. Other options are incorrect: A is false because traditional warehouses are relational; C is incorrect because lakehouses typically decouple compute and storage rather than coupling them; D is incorrect because lakehouses favor open storage formats (e.g., Parquet, Delta) rather than proprietary formats.
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