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DW-1: Introduction to Data Warehousing Overview What is Database What Is Data Warehousing Data Marts and Data Warehouses The Data Warehousing Process Data in a Data Warehouse What Is Database Before Now Program = Algorithm + Data Structure Application (Weblication) = Visual I/F + SQL Query + Database Database is Integrated Data from multiple file system data for OLTP Data Base (From Air Base?), DB, 데이타베이스, 자료기지(북한) Database and Data Model Computer Representation of Data for efficient understanding and processing Data Model based on Relationship modeling Relationship between record one-to-one(1:1), one-to-many(1:N), many-to-many(N:M) Hierarhical Model: Hierarchical Relationship, 1:N Network model: Network like relationship, N:M Relational Model: Use relation (table) for Relationship Object-Oriented data model: Complex object modeling SET type, Reference, List What Is Data Warehousing Defining Data Warehousing Operational Systems: A Transactional Solution Analytical Systems: A Data Warehousing Solution Comparing Transactional and Data Warehousing Solutions Defining Data Warehousing Business Intelligence Database Marketing: Personalized Product Especially S/W, Cocoon business etc. Electronic Commerce Data Warehouse: 자료 창고 for OLAP, Data Mining, DSS Knowledge Management Data Warehousing: Process to build Data Warehouse Defining Data Warehousing A Data Warehouse Is a Database That Contains: Enterprise data Integrated sets of historical data Subject-oriented, consolidated, consistent data Data structured for distribution and querying A Data Warehousing Solution Is a Process That: Retrieves and transforms data Manages the database Uses tools for building and managing the data warehouse Operational Systems: A Transactional Solution Track Individual Events Used for Real-time Data Entry and Editing Examples: Order-tracking applications Customer service applications Point-of-sale applications Service-based sales applications Banking functions Analytical Systems: A Data Warehousing Solution Assist with Strategic Decision Support Provide Different Levels of Analysis Allow Users to Navigate to Different Levels of Data Allow System Searches to Find New Relationships Examples: Spreadsheet-based applications Sales forecasting applications Comparing Transactional and Data Warehousing Solutions Transactional solutions Data warehousing solutions Update frequency Real-time Periodically Structured for Data integrity Ease in querying Optimized for Transaction performance Query performance Data Marts and Data Warehouses What Is a Data Mart Moving Data from a Data Warehouse to Data Marts Moving Data from Data Marts to a Data Warehouse What Is a Data Mart What Is a Data Mart A subset of a data warehouse Used in an enterprise Specific to a particular subject or business activity Why Build Data Marts Faster queries and fewer users Faster deployment time Integrated Data Marts Ensure consistent data Require advance planning Moving Data From a Data Warehouse to Data Marts Sales Mart Source 1 Source 2 Data Warehouse Source 3 Advantages Shared fields Common source Distributed processing Disadvantages Longer time to develop Financial Mart Customer Service Mart Moving Data from Data Marts to a Data Warehouse Source 1 Sales Mart Source 2 Financial Mart Source 3 Advantages Customer Service Mart Simpler and faster to implement Department-specific data Smaller hardware requirements Disadvantages Data duplication Incompatible data marts Data Warehouse The Data Warehousing Process Basic Elements of the Process Tools to Manage the Process Basic Elements of the Process Source OLTP Systems Data Marts Clients Data Warehouse 1 Retrieve Data 2 Transform Data 3 Populate Data Warehouse 4 Populate Data Marts 5 Query the Data Tools to Manage the Process SQL Server Data Transformation Services SQL Server OLAP Services Microsoft Repository Microsoft English Query PivotTable Service ETL process Extraction, Transformation, Loading Extraction: 추출 Transformation: 변환 Data modification, sorting, calculation etc Loading: 적재 Data retrieval from existing data source such as File, Table etc. Bulk, incremental loading from operational DB Time consuming process: may use special H/W Data in a Data Warehouse Data Characteristics Example of Organizing Data Data Characteristics Data characteristic Description Consolidated Enterprise-wide Consistent Within the data warehouse Subject-oriented Organized to user perspective Historical Snapshots over time Read-only Cannot update Summarized To appropriate level of detail Example of Organizing Data Monthly Southeast Regional Sales Report - May 1999 State City Units Sold Sales $ FL Miami 2,500 $12,850 FL Tampa 2,750 $14,135 5,250 $26,985 FL Totals GA Atlanta 3,200 $16,800 GA Savannah 1,725 $ 9,143 4,925 $25,943 1,900 $ 9,595 1,900 $ 9,595 12,075 $62,473 GA Totals SC Columbia SC Totals Southeast Region Total Data Warehouse Schema Example: Star schema A Example of Cube Browsing 1 Fact with 4 Dimension Table -- Sales_Fact, Product, Store, Time, Customer Drilling Down Drilling Down to products Drilling Down Drilling Down to the lowest level of Customer Dimension Rolling up Rolling up Review What Is Data Warehousing Data Marts and Data Warehouses The Data Warehousing Process Data in a Data Warehouse Data Warehouse will be more popular than DB?