IDIS 450 Final Exam Cummulative
Questions and Answers58
Data Analytics - ANSWERS-insight for making decisions
helps find meaningful patterns/knowledge in data
Intuition - ANSWERS--relies on repetition
-fast thinking
-if you can't repeat it then you can't be an expert at it
Analytics relies heavily on statistics and probability - ANSWERS--how likely something will
happen
-chance it won't occur
Analytics are never 100% guarantee - ANSWERS-outside factors can influence decision
business analytics - ANSWERS-fact based decision making based off data, information
technology computer based models, and statistical analysis/quantitative methods
applications of business analytics - ANSWERS-• Customer relationship
• Sports game strategies
• Pricing decisions
• Human resource planning
• Supply chain management
,• Financial and marketing
importance of business analytics - ANSWERS-•Strong relationship with profitability of business,
revenue of business, and shareholder return
•Enhances understanding of data
•Vital for businesses to remain competitive
•Enables creation of informative reports
Descriptive analytics - ANSWERS-•Uses data to understand past and present
•Summarizes data into meaningful charts and reports
•Identify patterns and trends in data
Predictive Analytics - ANSWERS-•Analyzes past performance
•Extrapolating to future
•Predicts risk
Prescriptive Analytics - ANSWERS-•Uses optimization techniques to identify best alternatives
•Often combined with predictive analytics to account for risk
types of business analytics - ANSWERS-•Descriptive
•Predictive
•Prescriptive
linear demand prediction model - ANSWERS-as prices increases, demand falls
-when should they discount and what should the discount be to create maximum profit
,example of predictive analytics
supply chain - ANSWERS--number of sales in region
-customer and product stratification
-where should we open new facilities
metrics - ANSWERS-used to quantify performance
measures - ANSWERS-numerical values of metrics
discrete metrics - ANSWERS-involve counting
•On time
•Not on time
•Number/proportion of on-time deliveries
continuous metrics - ANSWERS-measured on a continuum
• Delivery time
• Package weight
• Purchase price
purchase price - ANSWERS-average cost to me
4 types of data - ANSWERS-• Categorical/nominal
• Ordinal
• Interval
, • Ratio
categorical data - ANSWERS-• Data placed in categories according to a specified characteristic
• Bears no quantitative relationship
categorical data examples - ANSWERS-• Customers location
• Employee classification
ordinal data - ANSWERS-ranked or ordered according to some relationship with one another
-no fixed units of measurement
shows a relationship but has no scale of a relationship
ordinal data examples - ANSWERS-• College football rankings
• Survey responses
interval data - ANSWERS-ordinal data with constant differences between observations
• No true zero point
• Ratios not meaningful
interval data examples - ANSWERS-• Temperature readings
• SAT scores
ratio data - ANSWERS-continuous values and have a natural zero point
-meaningful ratios
Questions and Answers58
Data Analytics - ANSWERS-insight for making decisions
helps find meaningful patterns/knowledge in data
Intuition - ANSWERS--relies on repetition
-fast thinking
-if you can't repeat it then you can't be an expert at it
Analytics relies heavily on statistics and probability - ANSWERS--how likely something will
happen
-chance it won't occur
Analytics are never 100% guarantee - ANSWERS-outside factors can influence decision
business analytics - ANSWERS-fact based decision making based off data, information
technology computer based models, and statistical analysis/quantitative methods
applications of business analytics - ANSWERS-• Customer relationship
• Sports game strategies
• Pricing decisions
• Human resource planning
• Supply chain management
,• Financial and marketing
importance of business analytics - ANSWERS-•Strong relationship with profitability of business,
revenue of business, and shareholder return
•Enhances understanding of data
•Vital for businesses to remain competitive
•Enables creation of informative reports
Descriptive analytics - ANSWERS-•Uses data to understand past and present
•Summarizes data into meaningful charts and reports
•Identify patterns and trends in data
Predictive Analytics - ANSWERS-•Analyzes past performance
•Extrapolating to future
•Predicts risk
Prescriptive Analytics - ANSWERS-•Uses optimization techniques to identify best alternatives
•Often combined with predictive analytics to account for risk
types of business analytics - ANSWERS-•Descriptive
•Predictive
•Prescriptive
linear demand prediction model - ANSWERS-as prices increases, demand falls
-when should they discount and what should the discount be to create maximum profit
,example of predictive analytics
supply chain - ANSWERS--number of sales in region
-customer and product stratification
-where should we open new facilities
metrics - ANSWERS-used to quantify performance
measures - ANSWERS-numerical values of metrics
discrete metrics - ANSWERS-involve counting
•On time
•Not on time
•Number/proportion of on-time deliveries
continuous metrics - ANSWERS-measured on a continuum
• Delivery time
• Package weight
• Purchase price
purchase price - ANSWERS-average cost to me
4 types of data - ANSWERS-• Categorical/nominal
• Ordinal
• Interval
, • Ratio
categorical data - ANSWERS-• Data placed in categories according to a specified characteristic
• Bears no quantitative relationship
categorical data examples - ANSWERS-• Customers location
• Employee classification
ordinal data - ANSWERS-ranked or ordered according to some relationship with one another
-no fixed units of measurement
shows a relationship but has no scale of a relationship
ordinal data examples - ANSWERS-• College football rankings
• Survey responses
interval data - ANSWERS-ordinal data with constant differences between observations
• No true zero point
• Ratios not meaningful
interval data examples - ANSWERS-• Temperature readings
• SAT scores
ratio data - ANSWERS-continuous values and have a natural zero point
-meaningful ratios
