Data Management and Analytics Flashcards

What is the primary purpose of a data warehouse in an enterprise environment?

Answer: To consolidate historical data from multiple sources for analytical reporting

A data warehouse consolidates historical data from disparate sources into a centralized repository optimized for analytical queries and business intelligence reporting.

Which term describes the process of extracting data from source systems, transforming it into a usable format, and loading it into a target system?

Answer: ETL (Extract, Transform, Load)

ETL (Extract, Transform, Load) is the standard pipeline process that moves data from source systems, applies business rules and cleaning, then loads it into analytical targets.

What is data normalization in the context of relational database design?

Answer: Organizing data to reduce redundancy and improve data integrity

Database normalization organizes tables and relationships to minimize data redundancy and avoid update anomalies, improving overall data integrity.

Which type of database is best suited for storing and querying large volumes of unstructured or semi-structured data at scale?

Answer: NoSQL database

NoSQL databases (such as document, key-value, or graph stores) are designed for flexible schemas and horizontal scaling, making them well-suited for unstructured and semi-structured data.

What is a data lake, and how does it differ from a data warehouse?

Answer: A data lake stores raw data in native format at scale; a data warehouse stores processed, structured data optimized for queries

A data lake stores vast amounts of raw data in its native format until needed, while a data warehouse stores pre-processed, structured data organized for specific analytical use cases.

Which concept refers to the accuracy, completeness, consistency, and reliability of data throughout its lifecycle?

Answer: Data quality

Data quality encompasses dimensions such as accuracy, completeness, consistency, timeliness, and reliability, ensuring data is fit for its intended purpose.

In the context of the data management lifecycle, what does 'data archiving' primarily accomplish?

Answer: Moving infrequently accessed data to lower-cost storage while retaining it for compliance or future reference

Data archiving moves rarely accessed data to cost-effective storage tiers while preserving it for regulatory compliance, auditing, or potential future analytical use.