Chapter 13 The Data Warehouse Database Systems: Design, Implementation, and Management, Seventh Edition, Rob and Coronel

In this chapter, you will learn: How operational data and decision support data differ What a data warehouse is, how data for it are prepared, and how it is implemented What star schemas are and how they are constructed What data mining is and what role it plays in decision support Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

In this chapter, you will learn (continued): What online analytical processing (OLAP) is How SQL extensions are used to support OLAP-type data manipulations Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

The Need for Data Analysis Managers must be able to track daily transactions to evaluate how the business is performing By tapping into operational database, management can develop strategies to meet organizational goals Data analysis can provide information about short-term tactical evaluations and strategies Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

The Need for Data Analysis (continued) Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

The Need for Data Analysis (continued) Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

Decision Support Systems Decision support is methodology (or series of methodologies) designed to extract information from data and to use such information as a basis for decision making Decision support system (DSS) Arrangement of computerized tools used to assist managerial decision making within business Usually requires extensive data “massaging” to produce information Used at all levels within organization Often tailored to focus on specific business areas Provides ad hoc query tools to retrieve data and to display data in different formats Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

Decision Support Systems (continued) Composed of following four main components: Data store component Basically a DSS database Data extraction and data filtering component Used to extract and validate data taken from operational database and external data sources End-user query tool Used to create queries that access database End-user presentation tool Used to organize and present data Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

Decision Support Systems (continued) Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

Operational Data vs. Decision Support Data Mostly stored in relational database Optimized to support transactions representing daily operations DSS Data Give tactical and strategic business meaning to operational data Differs from operational data in following three main areas: Timespan Granularity Dimensionality Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

Operational Data vs. Decision Support Data (continued) Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

Operational Data vs. Decision Support Data (continued) Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

DSS Database Requirements A specialized DBMS tailored to provide fast answers to complex queries. Four main requirements: Database schema Data extraction and loading End-user analytical interface Database size Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

DSS Database Requirements (continued) Database schema Must support complex data representations Must contain aggregated and summarized data Queries must be able to extract multidimensional time slices Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

DSS Database Requirements (continued) Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

DSS Database Requirements (continued) Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

DSS Database Requirements (continued) Data extraction Should allow batch and scheduled data extraction Should support different data sources Flat files Hierarchical, network, and relational databases Multiple vendors Data filtering Must allow checking for inconsistent data Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

DSS Database Requirements (continued) End-user analytical interface One of most critical DSS DBMS components Permits user to navigate through data to simplify and accelerate decision-making process Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

DSS Database Requirements (continued) Database size In 2005, Wal-Mart had 260 terabytes of data in its data warehouses DBMS must support very large databases (VLDBs) Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

The Data Warehouse Integrated, subject-oriented, time-variant, nonvolatile collection of data that provides support for decision making Usually a read-only database optimized for data analysis and query processing Requires time, money, and considerable managerial effort to create Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

The Data Warehouse (continued) Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

The Data Warehouse (continued) Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

The Data Warehouse (continued) Data mart Small, single-subject data warehouse subset Each is more manageable data set than data warehouse Provides decision support to small group of people Typically lower cost and lower implementation time than data warehouse Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

DSS Architectural Styles Several are available Provide advanced decision support features Some capable of providing access to multidimensional data analysis Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

DSS Architectural Styles (continued) Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

Twelve Rules that Define a Data Warehouse Data warehouse and operational environments are separated Data warehouse data are integrated Data warehouse contains historical data over long time horizon Data warehouse data are snapshot data captured at given point in time Data warehouse data are subject oriented Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

Twelve Rules that Define a Data Warehouse (continued) Data warehouse data are mainly read-only with periodic batch updates from operational data No online updates allowed Data warehouse development life cycle differs from classical systems development Data warehouse contains data with several levels of detail: current detail data, old detail data, lightly summarized data, and highly summarized data Data warehouse environment is characterized by read-only transactions to very large data sets Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

Twelve Rules that Define a Data Warehouse (continued) Data warehouse environment has system that traces data sources, transformations, and storage Data warehouse’s metadata are critical component of this environment Data warehouse contains chargeback mechanism for resource usage that enforces optimal use of data by end users Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

Online Analytical Processing Advanced data analysis environment that supports decision making, business modeling, and operations research OLAP systems share four main characteristics: Use multidimensional data analysis techniques Provide advanced database support Provide easy-to-use end-user interfaces Support client/server architecture Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

Multidimensional Data Analysis Techniques Data are processed and viewed as part of a multidimensional structure Particularly attractive to business decision makers Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel

Multidimensional Data Analysis Techniques (continued) Augmented by following functions: Advanced data presentation functions Advanced data aggregation, consolidation and classification functions Advanced computational functions Advanced data modeling functions Database Systems: Design, Implementation, & Management, 7th Edition, Rob & Coronel