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MSIS 3223 Exam -1 WITH 100- CORRECT ANSWERS.
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MSIS 3223 Exam -1 WITH 100- CORRECT ANSWERS.
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EUNICEMSIS 3223 Exam #1 WITH 100% COMPLETE
ANSWERS
The use of data, information technology, statistical analysis, quantitative
Business Analytics methods, and mathematical or computer-based models to help managers gain
improved
insight about the business operations and make better, fact-based decisions.
Pricing (example of business analytics setting prices for consumer and industrial goods, government contracts,
application) and maintenance contracts
Customer segmentation (example of identifying and targeting key customer groups in retail, insurance, and credit
business analytics application) card industries
Merchandising (example of business determining brands to buy, quantities, and allocations
analytics application)
Location (example of business analytics finding the best location for bank branches and ATMs, or where to service
application) industrial equipment
Supply chain design (example of business determining the best sourcing and transportation options and finding the
analytics application) best delivery routes
Staffing (example of business analytics ensuring appropriate staffing levels and capabilities, and hiring the right people
application)
Health care (example of business analytics scheduling operating rooms to improve utilization, improving patient flow
application) and waiting times, purchasing supplies, and predicting health risk factors
reduced costs, better risk management, faster decisions, better productivity and
Benefits of analytics
enhanced bottom-line performance such as profitability and customer satisfaction.
lack of understanding of how to use analytics, competing business priorities,
Challenges of analytics insufficient analytical skills, difficulty in getting good data and sharing
information, and not understanding the benefits versus perceived costs of
analytics studies.
-IBM Cognos Express
Commercial software -SAS Analytics
-Tableau
1/6
, -Widely used
-Effective for manipulating data and developing and solving models
Spreadsheets
-Support powerful commercial add-ons
-Facilitate communication of results
the use of data to understand past and current business performance and
Descriptive analytics make informed decisions
-Example: Examine historical data fro similar products (price, units sold, advertising)
predict the future by examining historical data, detecting patterns or relationships
Predictive analytics in these data, and then extrapolating these relationships forward in time
-Example: Predict sales based on price
identify the best alternatives to minimize or maximize some objective
Prescriptive analytics
-Example: Find the best sets of pricing and advertising to maximize sales revenue.
Numbers or textual data that are collected through some type of measurement
Data
process.
Result of analyzing data; that is, extracting meaning from data to support
Information
evaluation and decision making.
refers to massive amounts of business data (volume) from a wide variety of
Big data sources (variety), much of which is available in real time (velocity), and much of
which is
uncertain or unpredictable (veracity).
Reliability Data are accurate and consistent
Validity Data correctly measures what it is supposed to measure.
-An abstraction or representation of a real system, idea, or object.
-Captures the most important features.
Model
-Can be written or verbal description, a visual representation, a
mathematical formula, or a spreadsheet.
- a logical or mathematical representation of a problem or business situation that
Decision model
can be used to understand, analyze, or facilitate making a decision
-Data - assumed to be constant
Inputs of decision models -Uncontrollable inputs - quantities that can change but cannot be controlled
-Decision options - controllable and selected at the discretion of the decision maker
Outputs of decision models Measures of performance or behavior
explain behavior and allow users to evaluate potential decisions by asking "what-
Descriptive models
if?" questions.
-focus on what will happen in the future.
Predictive models -developed by analyzing historical data and assuming that the past is
representative of the future.
Prescriptive models help decision makers identify the best solution to a decision problem.
finding values of decision variables that minimize (or maximize) something such
Optimization
as cost (or profit)
Objective function the equation that minimizes (or maximizes) the quantity of interest
Optimal solution values of the decision variables at the minimum (or maximum) point
-simplify a model and make it more tractable; that is, able to be easily analyzed
or solved.
Model assumptions -better characterize historical data or past observations.
-The task of the modeler is to select or build an appropriate model that
best represents the behavior of the real situation.
2/6
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