Flashcards

Data Warehousing

Extract Transform Load (ETL) processes

Understand the basics of Data Warehousing and ETL processes, build data pipelines to extract data from different sources, transform it, and load it into data warehouses for analysis.

5 minutes 5 Questions

Data Warehousing is a fundamental concept in the Big Data ecosystem, serving as a centralized repository that stores structured, semi-structured, and unstructured data from various sources for efficient analysis and reporting. Unlike operational databases that handle day-to-day transactions, data w…

Test mode:

Exam (Timed)

Practice (With explanations)

Start practice test

Big Data Engineer - Data Warehousing Example Questions

Test your knowledge of Data Warehousing

Question 1

What is the purpose of an ETL process in data warehousing?

To extract, transform, and load data from disparate sources into a common format for analysis and reporting To extract, translate, and load data from similar sources into a common format for analysis and reporting To extract, translate, and load data from disparate sources into a common format for analysis and reporting To extract, translate, and link data from disparate sources into a common format for analysis and reporting To extract, transform, and link data from disparate sources into a common format for analysis and reporting To extract, transform, and load data from similar sources into a common format for analysis and reporting

Correct Answer: To extract, transform, and load data from disparate sources into a common format for analysis and reporting

The ETL process is used to integrate data from multiple sources into a common format for analysis and reporting. It involves extracting data from the source systems, transforming it into the desired format, and loading it into the target data warehouse or destination systems. This process is essential for ensuring data consistency, accuracy, and completeness.

Question 2

What is a fact table in data warehousing?

A table that contains the quantitative data that is the focus of the analysis A table that contains the descriptive data for the dimensions A table that holds calculated values that are not part of any dimension A table that is used to link dimensions and fact tables A table that holds only high-cardinality attributes

Correct Answer: A table that contains the quantitative data that is the focus of the analysis

A fact table is a table that contains the quantitative data that is the focus of the analysis in a data warehouse. It holds the measures, which are numeric values that provide insights into business performance, and the foreign keys that link to the dimension tables.

Question 3

What is a cube in data warehousing?

A tool used for extracting data from source systems A process used for transforming data for loading into a data warehouse A table that holds fact data in a data warehouse A multidimensional data structure used for OLAP analysis A table that holds slowly changing dimension data

Correct Answer: A multidimensional data structure used for OLAP analysis

A cube is a multidimensional data structure used for OLAP analysis. It is organized into dimensions, measures, and hierarchies, allowing for flexible and efficient querying and analysis of large datasets.

🎓 Unlock Premium Access

Big Data Engineer + ALL Certifications

🎓 Access to ALL Certifications: Study for any certification on our platform with one subscription
951 Superior-grade Big Data Engineer practice questions
Unlimited practice tests across all certifications
Detailed explanations for every question
100% Satisfaction Guaranteed: Full refund if unsatisfied
Risk-Free: 7-day free trial with all premium features!