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