ADM 1370 Lecture Notes - Lecture 2: Software Framework, Terabyte, Data Mining

• School: University of Ottawa
• Department: Administration
• Course: ADM 1370
• Professor: Umar Ruhi

Document Summary

Data life cycle: data warehouse & olap. Indexing, searching, & querying: keyword based search, pattern matching. Knowledge discovery: data analytics, data mining. Interactive, exploratory analysis of multidimensional data from multiple perspectives using operations such as slice-and-dice, drill-down, & aggregate. Star schema cubes are stored in relational databases. Aggregates add up amounts by day, product | in sql: select date, sum(amt) from sale, group by date, prodid. Data mining: uses a variety of techniques to find patterns & relationships in large volumes of information & infers rules that predict future behaviour & guide decision making. Tools for deep down analysis of large pools of data: to find hidden patters, to predict future behaviour, to infer rules to guide decision-making. Data mining techniques make use of data in a data warehouse. Common forms of data-mining analysis capabilities include. = classification, cluster analysis, association detection (1) classification. Classes are pre-defined; assign each data point to 1 class.