Business Intelligence Using Power BI - Question Bank

 

Business Intelligence Using Power BI
Question Bank

---

Unit 1: Introduction to Power BI

1.     Trace the historical development of Power BI and discuss how it contributes to modern Business Intelligence practices.

2.     Describe the major capabilities and functionalities that make Power BI an effective BI tool.

3.     Examine the differences between Power BI Desktop and Power BI Service in terms of usage and purpose.

4.     Discuss the roles performed by various data professionals such as Data Analyst, Data Engineer, Power BI Developer, and Data Scientist within an analytics environment.

5.     Illustrate how Power BI supports organizations in analyzing data and presenting insights through visualization techniques.

---

Unit 2: Data Acquisition and Transformation

1.     Explain how different basic visual charts can be created in Power BI and discuss their practical applications.

2.     Describe the purpose of the Power Query Editor and outline the steps involved in transforming raw data.

3.     Discuss the concept of DAX (Data Analysis Expressions) and explain how it is used for calculations using any dataset.

4.     Analyze the different types of data sources that can be connected to Power BI for data acquisition.

5.     Explain the procedure for establishing connections between Power BI and cloud storage datasets (Drive) as well as web-based data sources.

6.     Discuss the importance of the Transform Data feature and how it supports data preparation.

7.     Explain how new fields can be created using Custom Columns and describe the role of Conditional Columns in data transformation.

8.     Describe the structure and functions of the Visualizations Pane in Power BI.

9.     Explain the purpose and key formatting options available in the Format Pane.

10. Explain merge, split, append, replace features in power bi

11. Explain Unpivot table feature in power bi

Unit 3: Exploratory Data Analysis (EDA)

1.      Exploratory Data Analysis (EDA) in Power BI helps in understanding data characteristics and identifying trends.
Explain the importance of EDA in Power BI with suitable examples.

2.      Descriptive statistics are used in Power BI to summarize data effectively.
Explain Mean, Median, Mode, and Standard Deviation and how they are used in Business Intelligence using Power BI.

3.      Data visualization in Power BI makes data interpretation easier.
Explain Histogram, Box Plot, and Scatter Plot in Power BI and how they help in analysis.

4.      Correlation analysis in Power BI helps in identifying relationships between variables.
Explain correlation and how scatter plots in Power BI support relationship analysis. 

6.      Outliers can significantly affect Power BI reports and dashboards.
Explain how outliers are detected and handled using Power BI visualization techniques.

7.      EDA is an important step before building dashboards in Power BI.
Justify this statement with suitable examples.

9.      A dataset of student performance is analyzed using Power BI.
Explain how EDA techniques help in identifying trends and patterns.

10.  EDA in Power BI helps in drawing insights and supporting business decisions.
Explain how conclusions and recommendations are derived using Power BI.

11.  A company uses Power BI for sales analysis across regions.
Explain how EDA techniques (descriptive statistics and visualization in Power BI) help in identifying patterns and business insights.

 Unit 4: Data Visualization

1. Designing effective dashboards in Power BI requires proper layout and visualization techniques.
   Explain layout and design principles for business reports with examples.
2. KPIs and business metrics are essential for decision-making in Business Intelligence using Power BI.
   Explain KPIs and how they are used in dashboards.
3. Choosing the right visual is important for effective data communication in Power BI.
   Explain how bar charts, line charts, and pie charts are used with examples.
4. A dataset contains sales data across months and regions.
   Explain how you will design a Power BI dashboard using appropriate visuals.
5. Advanced visuals(AI enabled features) in Power BI help in analyzing complex datasets.
   Explain the use of advanced visuals with examples.
6. A business requires customized reports.
   Explain how Power BI supports custom visualization using Python integration.
7. Interactive dashboards in Power BI help stakeholders make better decisions.
   Explain how interactive features improve dashboard usability.
8. A company wants real-time monitoring of business data.
   Explain how live dashboards and real-time data refresh are implemented in Power BI.
9. Data visualization plays a key role in Business Intelligence using Power BI.
   Explain how visualization helps in generating insights and decision-making.
10. Power BI dashboards must be user-friendly and informative. Analyze the key factors that make a dashboard effective.

13. A retail company uses Power BI for sales reporting.
    Explain how dashboards can be designed to show trends, KPIs, and insights.      

Case Studiees
 

Case Study 1

A retail company uses Power BI dashboards to analyze monthly sales data across different regions and product categories. The management has noticed fluctuations in sales and wants to understand trends, identify high-performing products, and improve decision-making. The dataset includes sales amount, region, product category, and time period.

Solve the following:

1. Explain the problem statement.

2. Suggest an appropriate title for the case study.

3. Define any two objectives.

4. State at least one hypothesis.

5. What type of analytics will you perform to solve the problem?

---

Case Study 2

A university is using Power BI reports to analyze student academic performance based on marks, attendance, and subject-wise scores. The management wants to identify patterns in performance, detect low-performing students, and improve academic outcomes using data visualization techniques.

Solve the following:

1. Explain the problem statement.

2. Suggest an appropriate title for the case study.

3. Define any two objectives.

4. State at least one hypothesis.

5. What type of analytics will you perform to solve the problem?

---

Case Study 3

A hospital uses Power BI dashboards to monitor patient data including age, disease type, treatment cost, and recovery time. The hospital administration wants to analyze trends in treatment effectiveness and cost distribution to improve healthcare services.

Solve the following:

1. Explain the problem statement.

2. Suggest an appropriate title for the case study.

3. Define any two objectives.

4. State at least one hypothesis.

5. What type of analytics will you perform to solve the problem?

---

Case Study 4

An e-commerce company is using Power BI visualization tools to analyze customer purchase behavior, product categories, and transaction history. The company wants to identify popular products, understand customer trends, and improve sales strategies.

Solve the following:

1. Explain the problem statement.

2. Suggest an appropriate title for the case study.

3. Define any two objectives.

4. State at least one hypothesis.

5. What type of analytics will you perform to solve the problem?

---

Case Study 5

A smart city project collects real-time traffic data such as vehicle count, congestion levels, and peak hours, and visualizes it using Power BI live dashboards. The city administration wants to monitor traffic conditions and reduce congestion using data-driven insights.

Solve the following:

1. Explain the problem statement.

2. Suggest an appropriate title for the case study.

3. Define any two objectives.

4. State at least one hypothesis.

5. What type of analytics will you perform to solve the problem?