Explain the concepts of Data, Information, and Knowledge in the context of Business Intelligence.
Business Intelligence - Elective VI Question Papers - SPPU University
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Business Intelligence - Elective VI Questions
Pre-rendered question cards from available structured metadata.
2024 May Jun ENDSEM
2024 Mar INSEM
2024 May Jun ENDSEM
INSEM
2024 Mar INSEM
12 Questions
Q1
15 Marks
Q1
·
b
·
5 Marks
Analyze a business scenario and identify how Business Intelligence tasks can be employed for strategic decision-making.
Q1
·
c
·
5 Marks
Evaluate the goals of Business Intelligence and its future trends.
Q2
15 Marks
Q2
·
a
·
5 Marks
Explain the connection between Business Intelligence and Decision Support System.
Q2
·
b
·
5 Marks
Propose a Business Intelligence architecture suitable for a specific industry and justify your choices.
Q2
·
c
·
5 Marks
Assess the impact of Business Intelligence on improving decision-making processes in organizations.
Q3
15 Marks
Q3
·
a
·
5 Marks
Explain how Logical Structures, such as ontology and frame, are used in BI modeling.
Q3
·
b
·
5 Marks
Identify the key components of Model Building in BI.
Q3
·
c
·
5 Marks
Utilize Business Process Model and Notation (BPMN) to model a complex business process in a given case study.
Q4
15 Marks
Q4
·
a
·
5 Marks
Elaborate on the significance of graph structures, specifically Business Process Model and Notation (BPMN), in BI modelling.
Q4
·
b
·
5 Marks
Describe the factors that contribute to the Quality of Models in Business Intelligence.
Q4
·
c
·
5 Marks
Develop a Model Presentation for a hypothetical business scenario and justify your design choices.
| Subject Name | Business Intelligence - Elective VI |
|---|---|
| Semester | VIII |
| Pattern Year | 2019 |
| Subject Code | 417533B |
| Max Marks | 30 |
| Total Questions | 4 |
| Duration | 1 Hour |
| Paper Number | [6270]-200 |
| Academic Year | B.E. |
| Branch Name | Artificial Intelligence and Data Science |
| Exam Type | INSEM |
| Exam Session | 2024 Mar INSEM |
| Watermark | ['CEGP013091', '49.248.216.238 27/03/2024 13:43:18 static-238'] |
ENDSEM
2024 May Jun ENDSEM
24 Questions
Q1
18 Marks
Q1
·
a
·
8 Marks
Evaluate the impact of Data Duplication on the overall performance and efficiency of a data warehouse
Q1
·
b
·
5 Marks
Explain the concepts of ETL Architecture, Extraction, Transformation, and Loading (ETL) in the context of Business Intelligence.
Q1
·
c
·
5 Marks
Explain the concept of Change Data Capture and its significance in data provisioning.
Q2
18 Marks
Q2
·
a
·
8 Marks
Analyse the role of Lookups in the transformation process of ETL.
Q2
·
b
·
5 Marks
Create a simplified data mart and explain its purpose in a BI system.
Q2
·
c
·
5 Marks
Describe the key components of Data Provisioning, including Data Quality, Data Profiling, and Data Enrichment.
Q3
17 Marks
Q3
·
a
·
8 Marks
Evaluate the effectiveness of different methods of Data discretization in improving the interpretability of data.
Q3
·
b
·
5 Marks
Describe the significance of Data Reduction in the context of large datasets, and explain the methods of Sampling.
Q3
·
c
·
4 Marks
Identify the types of data affected by noise and explain their impact on data quality.
Q4
17 Marks
Q4
·
a
·
8 Marks
Compare and contrast Feature Selection and Principal component Analysis (PCA) in terms of their applicability and limitations.
Q4
·
b
·
5 Marks
Differentiate between univariate, Bivariate and Multivariate analysis.
Q4
·
c
·
4 Marks
Discuss the importance of Data Exploration in the data analysis pipeline.
Q5
18 Marks
Q5
·
a
·
9 Marks
Consider the following dataset and we will find frequent item sets and generate association rules for them using apriori algorithm, consider minimum support count is 2 & minimum confidence is 60% TID Items T1 11, 12, 15 T2 12, 14 T3 12, 13 T4 11, 12, 14 T5 11, 13 T6 12, 13 T7 11, 13 T8 11, 12, 13, 15 T9 11, 12, 13
Q5
·
b
·
5 Marks
Define Bayesian methods and Logistic Regression in the context of classification.
Q5
·
c
·
4 Marks
List and explain the key components involved in the evaluation of regression models.
Q6
18 Marks
Q6
·
a
·
9 Marks
Explain logistic regression with example considering relevant variables and data.
Q6
·
b
·
5 Marks
Discuss the principles underlying the Apriori Algorithm for association rule mining.
Q6
·
c
·
4 Marks
Define Hierarchical methods in clustering and describe their characteristics.
Q7
17 Marks
Q7
·
a
·
9 Marks
Evaluate the benefits and challenges of integrating Cloud Computing with Business Intelligence.
Q7
·
b
·
5 Marks
Explain the importance of Business Intelligence in enhancing Customer Relationship Management strategies.
Q7
·
c
·
3 Marks
Provide examples of Business Intelligence applications in the Manufacturing Industry.
Q8
17 Marks
Q8
·
a
·
9 Marks
Create a plan for integrating Web 2.0 and Online Social Networking features into existing Business Intelligence systems.
Q8
·
b
·
5 Marks
Describe the impact of Business Intelligence on Healthcare Monitoring processes and outcomes.
Q8
·
c
·
3 Marks
List and briefly explain the applications of Business Intelligence in the Higher Education sector.
| Subject Name | Business Intelligence - Elective VI |
|---|---|
| Semester | VIII |
| Pattern Year | 2019 |
| Subject Code | 417533 B |
| Max Marks | 70 |
| Total Questions | 8 |
| Duration | 2½ Hours |
| Paper Number | [6263]-397 |
| Academic Year | B.E. |
| Branch Name | Artificial Intelligence and Data Science |
| Exam Type | ENDSEM |
| Exam Session | 2024 May Jun ENDSEM |
| Watermark | ['CEGP013091', '49.248.216.238 21/05/2024 14:02:19 static-238'] |
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