CDP Data Warehousing and Business Intelligence 1 — Questions and Answers
Question 1: What is the primary purpose of an Operational Data Store (ODS) in a data architecture?
- Long-term historical reporting
- Providing a near-real-time, integrated view of current operational data from multiple source systems (Correct answer)
- Storing raw unstructured data
- Running batch ETL processes
Correct answer: Providing a near-real-time, integrated view of current operational data from multiple source systems
An ODS integrates current operational data from multiple source systems to support short-term operational reporting and decision-making with near-real-time data.
Question 2: In data warehousing, what does ETL stand for?
- Execute, Transfer, Load
- Extract, Transform, Load (Correct answer)
- Extract, Test, Launch
- Evaluate, Transfer, Link
Correct answer: Extract, Transform, Load
ETL (Extract, Transform, Load) is the process of extracting data from source systems, transforming it for quality and consistency, and loading it into the target data warehouse.
Question 3: What distinguishes ELT from ETL in modern cloud data architectures?
- ELT does not require any data transformation
- ELT loads raw data into the target system first, then performs transformations using the target system's computing power (Correct answer)
- ELT is only used for unstructured data
- ELT stands for Evaluate, Link, Transfer
Correct answer: ELT loads raw data into the target system first, then performs transformations using the target system's computing power
ELT (Extract, Load, Transform) loads raw data into the target cloud data warehouse first, then leverages its massive parallel processing power to perform transformations in place.
Question 4: What is 'drill-down' in the context of OLAP and business intelligence?
- Navigating from summary-level data to more detailed, granular data (Correct answer)
- Combining data from multiple data sources
- Filtering data by a specific date range
- Exporting data to a CSV file
Correct answer: Navigating from summary-level data to more detailed, granular data
Drill-down in OLAP allows users to navigate from aggregate summary data to increasingly detailed, granular levels of data (e.g., from year → quarter → month).
Question 5: What is a data mart?
- A small, subject-oriented subset of a data warehouse focused on a specific business area or department (Correct answer)
- A marketplace for buying and selling data assets
- A type of real-time database
- A tool for data visualization
Correct answer: A small, subject-oriented subset of a data warehouse focused on a specific business area or department
A data mart is a subject-specific subset of a data warehouse (e.g., Sales, HR, Finance) designed to serve the reporting needs of a specific business unit or function.
Question 6: What does 'grain' mean in the context of a data warehouse fact table?
- The number of rows in the fact table
- The level of detail that each row in the fact table represents (Correct answer)
- The type of aggregation applied to measures
- The number of dimensions linked to the fact table
Correct answer: The level of detail that each row in the fact table represents
The grain of a fact table defines the most atomic level of detail that each row represents, such as one row per individual sales transaction line item.
CDP Data Warehousing and Business Intelligence 1
What is the primary purpose of an Operational Data Store (ODS) in a data architecture?