BUSINESS INTELLIGENCE, ANALYTICS, DATA SCIENCE EXAM
CHAPTER 1 T 10 WITH BEST APPROVED AND VERIFIED
QUESTIONS AND ANSWERS BEST GRADED 2025/2026
How does knowledge management contribute to decision support
--answer--It helps in organizing and utilizing information effectively.
What is a key advantage of computerized decision support systems?
--answer--They provide support anytime and anywhere.
What is the role of analytics in sports coaching?
--answer--To assist in making informed decisions regarding player performance and tactics.
What is one example of analytics application in college football?
--answer--Heat map zone analysis for passing plays.
What are some factors that could be part of a predictive model for season ticket renewals?
--answer--Fan engagement, previous renewal rates, and pricing strategies.
What techniques can football teams use for opponent analysis?
--answer--Statistical performance analysis, game film review, and player scouting.
What is the significance of overcoming cognitive limits in decision-making?
--answer--It allows for better processing and storage of information.
What is the relationship between business intelligence and artificial intelligence?
--answer--AI enhances the capabilities of BI by providing advanced data analysis and
predictive modeling.
What is the broad definition of Business Intelligence (BI)?
--answer--An umbrella term that combines architectures, tools, databases, analytical tools,
applications, and methodologies.
What is the narrow definition of Business Intelligence (BI)?
--answer--Descriptive analytics tools and techniques, such as reporting tools.
What are the two types of processing compared in Business Intelligence?
--answer--Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP).
,What is the goal of Online Transaction Processing (OLTP)?
--answer--Data capture.
What is the goal of Online Analytical Processing (OLAP)?
--answer--Decision support.
What are some examples of systems used in OLTP?
--answer--Operational databases, ERP (Enterprise Resource Planning), SCM (Supply Chain
Management), CRM (Customer Relationship Management).
What is the purpose of a Business Intelligence Competency Center?
--answer--To link BI to strategy and execution, encourage interaction between business user
communities and the IS organization, and serve as a repository of best BI practices.
What are some enablers of real-time Business Intelligence applications?
--answer--RFID (Radio-Frequency Identification), web services, and intelligent agents.
What are critical considerations when developing or acquiring BI systems?
--answer--Make versus buy decisions, BI shells, justification and cost-benefit analysis,
security, protection of privacy, and integration of systems and applications.
What is the definition of analytics in the context of BI?
--answer--The process of developing actionable decisions or recommendations for actions
based on insights generated from historical data.
What does analytics combine according to the Institute for Operations Research and
Management Science (INFORMS)?
--answer--Computer technology, management science techniques, and statistics to solve real
problems.
What is the relationship between Business Intelligence and business strategy?
--answer--BI is linked to the strategy and execution of strategy within an organization.
What is the significance of real-time BI applications?
--answer--They provide timely insights that can justify additional expenses for immediate
decision-making.
What is the historical timeline of Business Intelligence development?
--answer--It evolved through the 1970s, 1980s, and 1990s, leading to current practices.
What are the two main definitions of Business Intelligence?
,--answer--Broad definition includes various tools and methodologies; narrow definition
focuses on descriptive analytics.
What is the purpose of the multimedia exercise in Business Intelligence?
--answer--To provide case studies and scenarios for practical understanding of BI
applications.
How does BI serve different lines of business?
--answer--By advocating and encouraging standards of excellence in BI practices.
What is the importance of justification and cost-benefit analysis in BI systems?
--answer--It is a challenging endeavor that assesses the value and feasibility of BI
investments.
What are the emerging trends in Business Intelligence?
--answer--The emergence of real-time BI applications and the justification for their need.
What is the role of analytics in decision-making?
--answer--To develop actionable insights based on historical data.
What are some examples of Business Intelligence tools?
--answer--Architectures, analytical tools, databases, and applications.
What is the focus of Business Scenario Investigations (BSI)?
--answer--To analyze real-world business scenarios similar to Crime Scene Investigations
(CSI).
What is the significance of the architecture of Business Intelligence?
--answer--It provides a high-level framework for understanding how BI components interact.
What are the main functions served by a BI Competency Center?
--answer--Linking BI to strategy, encouraging user interaction, and disseminating best
practices.
What is descriptive analytics?
--answer--Descriptive analytics involves answering the question of what happened through
retrospective analysis of historic data.
What are the enablers of descriptive analytics?
--answer--The enablers include OLAP/DW, data visualization (dashboards and scorecards),
and descriptive statistics.
, What is the main goal of predictive analytics?
--answer--Predictive analytics aims to determine what is likely to happen in the future by
analyzing past data.
What are the enablers of predictive analytics?
--answer--The enablers include data mining, text mining/web mining, and forecasting (e.g.,
time series).
What is prescriptive analytics?
--answer--Prescriptive analytics aims to determine the best possible decision by using both
descriptive and predictive analytics to create alternatives and then identify the best one.
What are some enablers of prescriptive analytics?
--answer--Enablers include optimization, simulation, multi-criteria decision modeling, and
heuristic programming.
What is the relationship between analytics and data science?
--answer--Analytics is often contrasted with data science, where data scientists are the
practitioners of data science.
How does machine learning relate to predictive analytics?
--answer--Machine learning has become a substitute term for predictive analytics in some
contexts.
What fields prefer the term 'Data Science' over 'Business Analytics'?
--answer--Degree programs in computer science, statistics, and applied math prefer 'Data
Science', while business schools prefer 'Business Analytics'.
What is a key factor for success in data science projects?
--answer--Constant communication between business domain experts and data science
teams is critical to success.
What is one challenge organizations face regarding data?
--answer--Most organizations still face issues related to data, requiring the creation of a data
platform to share internal and external data.
What are the key steps for model development in analytics?
--answer--Data Analysis and Feature Engineering are key steps for model development.
How can an analytics platform impact product development?
CHAPTER 1 T 10 WITH BEST APPROVED AND VERIFIED
QUESTIONS AND ANSWERS BEST GRADED 2025/2026
How does knowledge management contribute to decision support
--answer--It helps in organizing and utilizing information effectively.
What is a key advantage of computerized decision support systems?
--answer--They provide support anytime and anywhere.
What is the role of analytics in sports coaching?
--answer--To assist in making informed decisions regarding player performance and tactics.
What is one example of analytics application in college football?
--answer--Heat map zone analysis for passing plays.
What are some factors that could be part of a predictive model for season ticket renewals?
--answer--Fan engagement, previous renewal rates, and pricing strategies.
What techniques can football teams use for opponent analysis?
--answer--Statistical performance analysis, game film review, and player scouting.
What is the significance of overcoming cognitive limits in decision-making?
--answer--It allows for better processing and storage of information.
What is the relationship between business intelligence and artificial intelligence?
--answer--AI enhances the capabilities of BI by providing advanced data analysis and
predictive modeling.
What is the broad definition of Business Intelligence (BI)?
--answer--An umbrella term that combines architectures, tools, databases, analytical tools,
applications, and methodologies.
What is the narrow definition of Business Intelligence (BI)?
--answer--Descriptive analytics tools and techniques, such as reporting tools.
What are the two types of processing compared in Business Intelligence?
--answer--Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP).
,What is the goal of Online Transaction Processing (OLTP)?
--answer--Data capture.
What is the goal of Online Analytical Processing (OLAP)?
--answer--Decision support.
What are some examples of systems used in OLTP?
--answer--Operational databases, ERP (Enterprise Resource Planning), SCM (Supply Chain
Management), CRM (Customer Relationship Management).
What is the purpose of a Business Intelligence Competency Center?
--answer--To link BI to strategy and execution, encourage interaction between business user
communities and the IS organization, and serve as a repository of best BI practices.
What are some enablers of real-time Business Intelligence applications?
--answer--RFID (Radio-Frequency Identification), web services, and intelligent agents.
What are critical considerations when developing or acquiring BI systems?
--answer--Make versus buy decisions, BI shells, justification and cost-benefit analysis,
security, protection of privacy, and integration of systems and applications.
What is the definition of analytics in the context of BI?
--answer--The process of developing actionable decisions or recommendations for actions
based on insights generated from historical data.
What does analytics combine according to the Institute for Operations Research and
Management Science (INFORMS)?
--answer--Computer technology, management science techniques, and statistics to solve real
problems.
What is the relationship between Business Intelligence and business strategy?
--answer--BI is linked to the strategy and execution of strategy within an organization.
What is the significance of real-time BI applications?
--answer--They provide timely insights that can justify additional expenses for immediate
decision-making.
What is the historical timeline of Business Intelligence development?
--answer--It evolved through the 1970s, 1980s, and 1990s, leading to current practices.
What are the two main definitions of Business Intelligence?
,--answer--Broad definition includes various tools and methodologies; narrow definition
focuses on descriptive analytics.
What is the purpose of the multimedia exercise in Business Intelligence?
--answer--To provide case studies and scenarios for practical understanding of BI
applications.
How does BI serve different lines of business?
--answer--By advocating and encouraging standards of excellence in BI practices.
What is the importance of justification and cost-benefit analysis in BI systems?
--answer--It is a challenging endeavor that assesses the value and feasibility of BI
investments.
What are the emerging trends in Business Intelligence?
--answer--The emergence of real-time BI applications and the justification for their need.
What is the role of analytics in decision-making?
--answer--To develop actionable insights based on historical data.
What are some examples of Business Intelligence tools?
--answer--Architectures, analytical tools, databases, and applications.
What is the focus of Business Scenario Investigations (BSI)?
--answer--To analyze real-world business scenarios similar to Crime Scene Investigations
(CSI).
What is the significance of the architecture of Business Intelligence?
--answer--It provides a high-level framework for understanding how BI components interact.
What are the main functions served by a BI Competency Center?
--answer--Linking BI to strategy, encouraging user interaction, and disseminating best
practices.
What is descriptive analytics?
--answer--Descriptive analytics involves answering the question of what happened through
retrospective analysis of historic data.
What are the enablers of descriptive analytics?
--answer--The enablers include OLAP/DW, data visualization (dashboards and scorecards),
and descriptive statistics.
, What is the main goal of predictive analytics?
--answer--Predictive analytics aims to determine what is likely to happen in the future by
analyzing past data.
What are the enablers of predictive analytics?
--answer--The enablers include data mining, text mining/web mining, and forecasting (e.g.,
time series).
What is prescriptive analytics?
--answer--Prescriptive analytics aims to determine the best possible decision by using both
descriptive and predictive analytics to create alternatives and then identify the best one.
What are some enablers of prescriptive analytics?
--answer--Enablers include optimization, simulation, multi-criteria decision modeling, and
heuristic programming.
What is the relationship between analytics and data science?
--answer--Analytics is often contrasted with data science, where data scientists are the
practitioners of data science.
How does machine learning relate to predictive analytics?
--answer--Machine learning has become a substitute term for predictive analytics in some
contexts.
What fields prefer the term 'Data Science' over 'Business Analytics'?
--answer--Degree programs in computer science, statistics, and applied math prefer 'Data
Science', while business schools prefer 'Business Analytics'.
What is a key factor for success in data science projects?
--answer--Constant communication between business domain experts and data science
teams is critical to success.
What is one challenge organizations face regarding data?
--answer--Most organizations still face issues related to data, requiring the creation of a data
platform to share internal and external data.
What are the key steps for model development in analytics?
--answer--Data Analysis and Feature Engineering are key steps for model development.
How can an analytics platform impact product development?
