OPRE 3333 Lecture Notes - Lecture 1: Bar Chart, Sparkline, Time Series
25 Jun 2018
School
Department
Course
Professor
CH 1 + CH 3 INTRO & DATA VISUALIZATION
Business Analytics: an objective scientific process of transforming data into insightful decision making.
Uses data-driven/ fact-driven decision making.
Managers plan, coordinate and organize.
◦ Strategic decisions : higher-level issues abt overall direction of company , 3-5 yrs.
Tactical decisions:◦ how the organization should achieve the goals and objectives set by its strategy,
midlevel, 1 yr.
Operational decisions: operation managers run day to day operations.◦
Problem Solving and Decision Making
1. Recognizing the problem: a gap between what is happening and what we think should be
happening.
2. Defining the problem: complex to define a problem if many courses of action, several competing
objectives, external groups, time constraints etc.
3. Structuring the problem: stating goals, objectives, possible decisions, identifying restrictions and
defining clear metrics and acquiring data.
4. Analyzing the problem : experimentation (trial and error), statistical analysis, or a solution process.
5. Interpreting results and making a decision: Understand limitations and model assumptions
6. Implementing the solution : is the solution logical, does it work in real world, and provide adequate
training and resources to make this possible.
Models:
Mathematical modeling- Accurately represent reality, gives insight on info, saves $ and time and useful
to communicate problems.
Decision model- used to understand, analyze, or facilitate decision making.
- types of input
1) data (accurate or trash in-trash out)
2) external variables (inflation, demand)
3) decision variables (controllable)
- output
1) Performance measures.
2) behavioral measures.
Analytics
Descriptive Analytics- describes what has happened in the past. Exs: data queries, reports, descriptive
statistics, data visualization, data-mining techniques
Predictive Analytics- uses past data to predict the future or evaluate the impact of one variable or
another.
Exs: Linear regression, time series analysis, some data-mining techniques, and simulation are part of
this category. There is uncertainty and risk.
Prescriptive Analytics- Indicate the best course of action to take, the best possible
decision. Exs: optimization and decision analysis.
Objective function - the equation that minimizes (or maximizes) the quantity of interest.
find more resources at oneclass.com
find more resources at oneclass.com
Document Summary
Ch 1 + ch 3 intro & data visualization. Business analytics: an objective scientific process of transforming data into insightful decision making. Managers plan, coordinate and organize: strategic decisions : higher-level issues abt overall direction of company , 3-5 yrs. how the organization should achieve the goals and objectives set by its strategy, Operational decisions: operation managers run day to day operations. midlevel, 1 yr. Mathematical modeling- accurately represent reality, gives insight on info, saves $ and time and useful to communicate problems. Decision model- used to understand, analyze, or facilitate decision making. Descriptive analytics- describes what has happened in the past. Exs: data queries, reports, descriptive statistics, data visualization, data-mining techniques. Predictive analytics- uses past data to predict the future or evaluate the impact of one variable or another. Exs: linear regression, time series analysis, some data-mining techniques, and simulation are part of this category. Prescriptive analytics- indicate the best course of action to take, the best possible decision.
