INFO 2020 Lecture 1: Lecture 1 Chapter 1
3 Jan 2017
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Document Summary
Business analytics: scientific process of transforming data into insight to making better decisions. Descriptive analytics: encompasses the set of techniques that describes what has happened in the past: data queries, reports, descriptive stats, data visualization, data-mining techniques, basic what-if spreadsheet models. Data query: a request for information with certain characteristics from a database. Techniques: linear regression, time series analysis, data mining to find patterns or relationships, 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: 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. Big data: a set of data that cannot be managed, processed, or analyzed with commonly available software in a reasonable amount of time: four vs of big data:
