INFO 2020 Lecture 1: Lecture 1 Chapter 1

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INFO 2020 Lecture 1
Business analytics: scientific process of transforming data into insight to making better
decisions
A Categorization of Analytical Methods and Models:
Descriptive analytics: encompasses the set of techniques that describes what has
happened in the past
o Data queries
o Reports
o Descriptive stats
o Data visualization
o Data-mining techniques
o Basic what-if spreadsheet models
Data query: a request for information with certain characteristics from a database
Data dashboards
Predictive analytics: consists of techniques that use models constructed from past data
to predict the future or ascertain the impact of one variable on another
o Survey data and past purchase behavior to predict the market share of a new
product
Techniques:
o Linear regression
o Time series analysis
o Data mining to find patterns or relationships
o Simulation: the use of probability and stats to construct a computer model to
study the impact of uncertainty on a decision
Prescriptive Analytics: indicates a best course of action to take
o Optimization models: models that give the best decision subject to constraints of
the situation
Portfolio models finance uses historical investment return data to
determine the mix of investments that yield the highest return
Supply network design models operations
Price markdown models retailing uses historical data to yield revenue-
maximizing discount levels and the time of discount offers when goods
have not sold as planned
o Simulation optimization: combines the sue of probability and statistics to model
uncertainty with optimization techniques to find good decision in highly complex
and highly uncertain
Big Data: a set of data that cannot be managed, processed, or analyzed with commonly
available software in a reasonable amount of time
o Four Vs of Big Data:
Volume terabytes to exabytes of existing data to process
Velocity streaming data, milliseconds to seconds to respond
Variety structured, unstructured, text, multimedia
Veracity uncertainly due to data inconsistency and incompleteness,
ambiguities, latency, deception, model approximations
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