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Lecture Database design, application development and administration - Chapter 16: Data warehouse technology and management

Chapter 16 - Data warehouse technology and management. This chapter presents the technology and management of data warehouses to satisfy the requirements of decision support. Data warehouse technology complements and extends relational database technology beyond online transaction processing and simple query capabilities such as the GROUP BY clause in SQL. | Chapter 16 Data Warehouse Technology and Management Welcome to Chapter 16 on Data Warehouse Technology and Management - Data warehouse: - Supports tactical (medium term) and strategic (long-term) decision making - New development in the 1990s: new technologies, architectures to apply technology Objectives: - Understand differences between transaction processing and decision support requirements - Learn the basic terminology - Gain insight about architectures in which to apply DW technology - Learn operators to manipulate data cubes and data modeling techniques to define them - Learn to use Relational DBMS features for data warehouses - Describe processes to populate and refresh data warehouses Outline Basic concepts and characteristics Business architectures and applications Data cube concepts and operators Relational DBMS features Maintaining a data warehouse Concepts and characteristics: - Transaction processing versus decision support processing - Defining characteristics of data warehouses Business architectures and applications: - Architectures: Enterprise data model, 2 tier, 3 tier, and bottom-up, maturity model - Data mining: adapt data warehouses to find hidden patterns in data - Applications: retail, telecommunications, insurance Data cube concepts and operators: - Examples and terminology - Operators Relational DBMS features - Relational data modeling - Dimension representation - GROUP BY extensions for subtotal calculation - Materialized views and query rewriting - DBMS architectures: ROLAP, MOLAP, HOLAP Maintaining data warehouses: - Sources of data - Workflows for maintaining a data warehouse - Managing the refresh process Comparison of Environments Transaction processing Uses operational databases Short-term decisions: fulfill orders, resolve complaints, provide staffing Decision support processing Uses integrated and summarized data Medium and long-term decisions: capacity planning, store locations, new lines of business Transaction processing: - . | Chapter 16 Data Warehouse Technology and Management Welcome to Chapter 16 on Data Warehouse Technology and Management - Data warehouse: - Supports tactical (medium term) and strategic (long-term) decision making - New development in the 1990s: new technologies, architectures to apply technology Objectives: - Understand differences between transaction processing and decision support requirements - Learn the basic terminology - Gain insight about architectures in which to apply DW technology - Learn operators to manipulate data cubes and data modeling techniques to define them - Learn to use Relational DBMS features for data warehouses - Describe processes to populate and refresh data warehouses Outline Basic concepts and characteristics Business architectures and applications Data cube concepts and operators Relational DBMS features Maintaining a data warehouse Concepts and characteristics: - Transaction processing versus decision support processing - Defining characteristics of data .