Data Warehouse

Knowledge Discovery Process

OLTP & OLAP

联机事务处理（OLTP, online transactionalprocessing）系统：涵盖组织机构大部分的日常操作，purchasing, inventory, banking,manufacturing, payroll, registration, accounting联机分析处理（OLAP, online analyticalprocessing）系统：以不同的格式组织和提供数据，以满足不同用户的各种需求，为数据分析和决策方面提供服务。 Distinct features (OLTP vs. OLAP): User and system orientation: customer vs. market Data contents: current, detailed vs. historical, consolidated View: current, local vs. evolutionary, integrated Access patterns: update vs. read-only but complex queries

Data Warehouse

DBMS— tuned for OLTP: access methods, indexing, concurrency control,recoveryWarehouse—tuned for OLAP: complex OLAP queries, multidimensionalview, consolidation Data Warehouse: 数据仓库将分布在企业网络中不同信息岛上的业务数据集成到一起，存储在一个单一的集成关系型数据库中，利用这样的集成信息，可方便用户对信息访问，可使决策人员对一段时间内的历史数据进行分析，研究事务的发展走势。A data warehouse is a subject-oriented, integrated,time-variant, and nonvolatile collection of data in supportof management’s decision-making process.” — W. H.Inmondata stored in data warehouse has been processedafter extracation, cleaning, transformation, load(sort, summarize...) and refresh.Data Warehouse model :dimensions and measures, you can locate some data by dimension and see the data by measures Conception model :star schema,snowflake schema(a refinement of star schema),fact constellations(a collection of stars) Example of Star Schema: Typical OLAP Operations :Roll up: summarize data by climbing up hierarchy or by dimension reduction, you can roll up to all to reduce a dimensionDill down:reverse of Roll-up, from higher level summaryto lower level summary or detailed dataSlice and dice:project and selectPriot(rotate):reorient the cube, visualization, 3D to series of 2D planes.

参考

中国科学院大学《数据挖掘》课程slices