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Chapter 1 Introduction to Business Analytics Data Analytics questions with right answers. $9.39   Add to cart

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Chapter 1 Introduction to Business Analytics Data Analytics questions with right answers.

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  • Course
  • Business Analytics
  • Institution
  • Business Analytics

Chapter 1 Introduction to Business Analytics Data Analytics questions with right answers.

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  • August 26, 2024
  • 7
  • 2024/2025
  • Exam (elaborations)
  • Questions & answers
  • Business Analytics
  • Business Analytics
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Professorkaylee
Chapter 1 Introduction to Business
Analytics Data Analytics questions with
right answers.

Business Analytics (BA) ANS - uses data and statistical methods to gain insight into the data and provide
decision makers with information they can act on.



Pricing ANS - Setting prices for consumer and industrial goods, government contracts, and maintenance
contracts.



Customer Segmentation ANS - identifying and targeting key customer groups in retail, insurance, and
credit card industries.



Merchandising ANS - determining brands to buy, quantities, and allocations.



Location ANS - Finding the best location for bank branches and ATMS, or where to service industrial
equipment.



Social Media ANS - Understand trends and customer perceptions; assist marketing mangers and
product designers.



Statistics = Business Intelligence/ Information Systems ANS - Data Mining



Statistics = Modeling and Optimization ANS - Simulation and Risk



Business Intelligence/ Information Systems = Modeling and Optimization ANS - What if?



Statistics = Modeling and Optimization = Business Intelligence/ Information Systems ANS - Visualization

, Benefits of Business Analytics ANS - -Reduced costs

-Better risk management

-Faster decision making

-Better productivity

-Enhanced bottom-line performance such as profitability and customer satisfaction.



Challenges of Business Analytics ANS - -Lack of understanding of how to use analytics

-Competing business priorities

-Insufficient analytical skills

-Difficulty in getting good data and sharing information, and not understanding the benefits versus
perceived costs of analytics studies. *Not all data is clean



Descriptive Analytics ANS - The use of data to understand past and current business performance and
make informed decisions.



Predictive Analytics ANS - Predict the future by examining historical data, detecting patterns or
relationships in these data, and then extrapolating these relationships forward in time.

Example: Regression to predict future sales.



Prescriptive Analytics ANS - Identify the best alternatives to minimize or maximize some objective.*
Linear programing

-The prescriptive decision model helps decision makers identify the best solution.



IBM Cognos Express ANS - An integrated business intelligence and planning solution designed to meet
the needs of midsize companies, provides reporting, analysis, dashboard, scorecard, planning, budgeting
and forecasting capabilities.



SAS Analytics ANS - Predictive modeling and data mining, visualization, forecasting, optimization and
model management, statistical analysis, text analytics, and more.



Tableau Software, Power BI ANS - Simple drag and drop tools for visualizing data from spreadsheets
and other databases.

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