Skip to main content

10 Multiple Choice Questions (MCQs) related to Data Modeling in Power BI

10 Multiple Choice Questions (MCQs) related to Data Modeling in Power BI



1. What is the primary purpose of data modeling in Power BI?

A) To create visualizations only
B) To structure relationships between tables for efficient analysis
C) To import data from external sources
D) To replace the need for SQL databases

Answer: B) To structure relationships between tables for efficient analysis


2. Which statement is true about fact tables and dimension tables?

A) Fact tables store descriptive attributes, while dimension tables store numeric data
B) Dimension tables store descriptive attributes, while fact tables store numeric data
C) Both fact and dimension tables store only numerical data
D) Fact tables store unstructured data

Answer: B) Dimension tables store descriptive attributes, while fact tables store numeric data


3. What is the key advantage of using a Star Schema in Power BI?

A) Reduces data redundancy but increases query complexity
B) Improves query performance and simplifies relationships
C) Requires more relationships to connect tables
D) Avoids the need for a date dimension

Answer: B) Improves query performance and simplifies relationships


4. In Power BI, what type of relationship is most commonly used between a fact table and a dimension table?

A) One-to-One (1:1)
B) One-to-Many (1:)
C) Many-to-Many (
:*)
D) Circular Relationship

Answer: B) One-to-Many (1:*)


5. What is cardinality in Power BI data modeling?

A) The number of visualizations on a dashboard
B) The number of rows in a dataset
C) The uniqueness of values in a column and its impact on performance
D) The way colors are represented in charts

Answer: C) The uniqueness of values in a column and its impact on performance


6. How can you create a Date Dimension in Power BI?

A) Using SQL scripts only
B) Using the CALENDAR() or CALENDARAUTO() DAX functions
C) By manually entering dates into an Excel file
D) By creating multiple relationships between tables

Answer: B) Using the CALENDAR() or CALENDARAUTO() DAX functions


7. What is the primary difference between a calculated column and a measure in Power BI?

A) Calculated columns are stored in the table, while measures are dynamically calculated
B) Measures require additional storage, while calculated columns do not
C) Calculated columns cannot be created using DAX
D) Measures can only be used in Power Query

Answer: A) Calculated columns are stored in the table, while measures are dynamically calculated


8. How can Many-to-Many relationships be handled in Power BI?

A) By creating a bridge table
B) By duplicating the dimension tables
C) By using the SUM function in DAX
D) By creating One-to-One relationships

Answer: A) By creating a bridge table


9. Which of the following is NOT a method to optimize Power BI data models?

A) Removing unnecessary columns
B) Using a Snowflake Schema instead of a Star Schema
C) Reducing cardinality in high-cardinality columns
D) Using pre-aggregated data

Answer: B) Using a Snowflake Schema instead of a Star Schema


10. What function is used to implement Row-Level Security (RLS) dynamically?

A) CALCULATE()
B) FILTER()
C) USERPRINCIPALNAME()
D) RELATEDTABLE()

Answer: C) USERPRINCIPALNAME()

Comments

Popular posts from this blog

Free Udemy Course for PowerBI

Free Udemy Course for PowerBI Get This Course for Free. Create beautiful dashboards instead of boring spreadsheets and slides. Make an involving presentation based on an interactive visual story. Create visualizations without programming skills. Learn some interesting tips for simply working with Power BI. Get this course for free. Basic Data Connection: Students will learn how to connect Power BI to simple data sources, gaining an understanding of basic data import techniques. Introductory Data Cleaning: Learners will be introduced to the Power Query Editor for basic data cleaning tasks, such as removing duplicates and filtering data. Fundamentals of Data Modeling: Participants will learn the basics of creating data models in Power BI, including simple relationships between tables. Basic DAX Formulas and Visualizations: Students will acquire foundational skills in writing simple DAX formulas and creating basic reports. Understanding the overall life cycle of building a Power BI Report...

Is Web Scraping Illegal and How Can We Do It?

Is Web Scraping Illegal and How Can We Do It? Web Scraping Course. Web scraping is not illegal by default, but its legality hinges on the method employed and adherence to applicable laws and website terms of service.  Below is a summary of legal considerations and guidelines for responsible web scraping: Legal Considerations: Terms of Service (ToS): Website ToS dictate the permissible use of their content. Some explicitly forbid web scraping, and violation of these terms could lead to legal repercussions. Copyright Law: Website content is often under copyright protection. While raw data and facts are not copyrightable, their creative presentation might be. Unauthorized scraping of significant amounts of such content could constitute copyright infringement. Computer Fraud and Abuse Act (CFAA): In the U.S., the CFAA outlaws unauthorized computer and system access. Scraping in contravention of website ToS may breach this act. Data Protection Laws: Web scraping may fall under data ...

Connecting Power BI to Azure Data Lake: Streamlining Big Data Analytics

Connecting Power BI to Azure Data Lake: Streamlining Big Data Analytics Azure Data Lake and Power BI provide a powerful combination for businesses to handle and analyze large datasets efficiently. Here’s a step-by-step breakdown of how connecting Power BI to Azure Data Lake helps streamline big data analytics. 1. What is Azure Data Lake? Azure Data Lake is a cloud-based storage solution designed to handle large volumes of structured and unstructured data. It provides highly scalable and cost-effective storage, making it an ideal choice for big data projects, data lakes, and large-scale analytics. 2. Benefits of Connecting Power BI to Azure Data Lake Handling Large Datasets : Power BI’s integration with Azure Data Lake allows users to work with large datasets without needing to import all the data into Power BI. Instead, users can connect and query data directly. Scalable Analytics : Azure Data Lake’s ability to scale horizontally ensures that it can handle growing volumes of data se...