Foundations of Data Lakes: Concepts and Applications Quiz

1. Definition of a Data Lake

   Which of the following best describes a data lake in the context of data storage technologies?

   1. A large, scalable repository that stores structured, semi-structured, and unstructured data in its raw form
   2. A system designed specifically for managing only relational data tables
   3. A tool used exclusively for real-time analytics processing data streams
   4. A secure place to store only encrypted documents for regulatory compliance
   5. A legacy framework for handling only batch-processed numeric data

2. Purpose of Data Lakes

   What is a primary reason organizations use data lakes in their data architecture?

   1. To provide flexible storage that allows data to be kept in its original format until needed for analysis
   2. To replace all backup systems with faster tape-based solutions
   3. To convert unstructured text into relational tables during data ingestion
   4. To prevent users from accessing any form of historical data
   5. To only support small datasets that require frequent deletion

3. Differences Between Data Lakes and Data Warehouses

   How does a data lake differ from a traditional data warehouse when handling diverse data types?

   1. A data lake can store images, videos, and logs alongside tables, while a data warehouse typically stores only structured data
   2. A data lake only accepts data after it has been cleaned and transformed
   3. A data lake performs faster analytics exclusively on numeric data
   4. A data warehouse freely stores raw video files and binary objects
   5. A data lake requires every dataset to fit a predefined schema

4. Example Use Case

   If a company wants to collect data from sensors, web logs, and social media posts for future analysis, which storage solution is most suitable?

   1. A data lake, because it can accommodate various formats without immediate processing
   2. A relational database, because it automatically parses unstructured data
   3. A flat file server, since it organizes all content in fixed schemas
   4. A metadata repository, restricting access to structured tables only
   5. A data ring, which is designed for streaming data only

5. Data Lake Challenges

   What is a common challenge organizations face when implementing data lakes?

   1. Ensuring data governance and quality due to storing diverse raw data
   2. Converting all files to binary code before storage
   3. Restricting access so strictly that no analysis is possible
   4. Enforcing single-user access at all times
   5. Only allowing text data to be ingested