MIS 111 Lecture Notes - Lecture 25: Data Mining, Data Warehouse, Big Data

• School: University of Arizona
• Department: Management Info Systems Main
• Course: MIS 111
• Professor: ALL

Document Summary

Kids in school could track grades with big data. Probabilistic cause crime you could commit but haven"t yet. Data warehouse: large multi-dimensional datasets, integrates information from independent (standalone) applications. Data mining ethical concerns will impact the way that data can be analyzed, ownership (intellectual property) issues. European data laws will have implications on us. Often data included in a data warehouse cannot legally be used in decision making process. 1. classification category of data (sex, race, age income etc. ) is there a pattern. 2. clustering groups of data, patterns around something, responding based on whats happening. 3. association a implies b, recommendation systems are in retail sales, upset someone based on associated sell, typically bought contemporaneously where timing is right. 4. sequencing closely relate dot one another. 5. forecasting thinking about pattern of data, drawing a regression line and finding a pattern in the data.