ADM 1370 Lecture Notes - Lecture 2: Data Warehouse, Online Analytical Processing, Data Mining
Document Summary
Business & commerce: corporate sales, stock market transactions, census, airline traffic, , humanities and social sciences, scanned books, historical documents, social interactions data. Entertainment: internet images, hollywood movies, mp3 files, . Medicine: mri & ct scans, patient records, . Science: data bases from astronomy, genomics, environmental data, transportation data, Aggregation and reports: data warehouse and olap. Indexing, searching, and querying: keyword based search, pattern matching. Interactive, exploratory analysis of multidimensional data from multiple perspectives using operations such as slice-and-dice, drill-down, and aggregate. Tools for deep down analysis of large pools of data: to find hidden patters, to predict future behavior, to infer rules to guide decision-making. Data mining techniques make use of the data in a data warehouse. Data-mining uses a variety of techniques to find patterns and relationships in large volumes of information and infers rules that predict future behaviour and guide decision making. Common forms of data-mining analysis capabilities include: classification, cluster analysis, association detection.
