Describe Data Aggregation Topologies (warehouses, Data Lakes, Lakehouses) CERTIFIED-AI-EXPERT Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   What is a common limitation of a data lake for AI data aggregation?

   • AIt requires a predefined schema for all data, making it inflexible
   • BIt lacks the ACID transaction support and data governance of a warehouse
   • CIt is expensive to scale storage to large volumes of data
   • DIt cannot store unstructured data such as images and videos
   Reveal Solution Discussion Select an answer first
2. 7foundation · easy

   Which use case is a lakehouse particularly well-suited for?

   • AReplacing all transactional databases in an organization
   • BProviding a low-cost archive for data that is never accessed
   • CStoring raw, unprocessed data with no need for querying
   • DSupporting both BI reporting and machine learning on the same data
   Reveal Solution Discussion Select an answer first
4. 8foundation · easy

   What is the primary advantage of a lakehouse architecture over a traditional data lake?

   • AIt eliminates the need for any data governance or security measures
   • BIt adds ACID transactions and schema enforcement on top of data lake storage
   • CIt requires all data to be stored in a columnar format
   • DIt replaces the need for a data warehouse entirely, with no overlap in use cases
   Reveal Solution Discussion Select an answer first
5. 9expert · hard

   A company has a data lake with raw sensor data. They want to enable BI dashboards that require ACID transactions and schema enforcement. They also want to keep the raw data available for data scientists. The company is considering adding a lakehouse layer, using a separate warehouse, or using external tables. Which approach best meets all requirements?

   • AUse a separate warehouse
   • BKeep the data lake as is
   • CUse external tables
   • DAdd a lakehouse layer
   Reveal Solution Discussion Select an answer first
6. 10foundation · easy

   What is a key characteristic of a data lake's storage approach?

   • AIt stores data in its raw, native format without requiring a predefined schema
   • BIt is optimized for high-performance transactional processing
   • CIt requires all data to be transformed into a tabular format before storage
   • DIt enforces a strict schema at the time of data ingestion
   Reveal Solution Discussion Select an answer first