1. Database – Part 2b Dr. V.T. Raja Oregon State University External References/Sources: Data Warehousing – Sakthi Angappamudali at Standard Insurance; BI – Business Week; Lee Martin at Hitachi Consulting

2. Outline Some database trends (past and recent) Why learn about databases?

3. Some Database Trends Centralized and Distributed databases Online Transaction/Analytical Processing (OLTP/OLAP) Data Warehouse and Data Marts Data Mining, Business Intelligence (BI) and Analytics

4. Centralized and Distributed databases Centralized Databases Advantages/Disadvantages? Distributed Databases Partitioned Databases Data spread across two or more smaller databases Connected via communication devices Replicated Databases Partially replicated databases Fully replicated databases Advantages/Disadvantages?

5. The Decision Making Roadmap Transaction Systems Decision Support Systems Executive Information Systems Business Planning RUN MANAGEGROW Users Knowledge Brokers Management Operational Functional Current Detailed Multi- Dimensional History Summary Analyze What If Scenarios History Detailed DataInformation Knowledge VisionActions

6. On-line Transaction Processing (OLTP) and On-line Analytical Processing (OLAP) OLTP: Immediate processing/analysis and handling of multiple concurrent transactions from customers/users Example: OLAP: Capability for manipulating and analyzing large volumes of data from multiple perspectives (multidimensional analysis) Example:

7. Data Warehouse Large repository of detailed and summary data used to support the strategic decision making process for the enterprise Stores current and historical data (internal and external) Integrates data from organization’s disparate information systems used by functional units Involve hundreds of gigabytes, and terabytes of data Run on very powerful computers Expensive

8. Design Mapping Design Mapping OLTP Systems Functional IS External Data OLTP - Raw Detail No/Minimal History DW-Integrated Scrubbed History Summaries Targeted Specialized (OLAP) OLTP, DW and DM - Data Characteristics Extract Scrub Transform Extract Scrub Transform Central Repository Load Index Aggregation Load Index Aggregation Data Warehouse Data Mart Replication Data Set Distribution Replication Data Set Distribution End User Workstations Data Warehousing Process

9. Data Mart A small data warehouse containing only a portion of the organization’s data for a specified function or population of users. It is a subset of a data warehouse (e.g., marketing/sales data mart)

10. Individual Architected Data Marts Common Logical Subject Area ERD Common Business Dimensions Common Business Rules Common Business Metrics Glossary Sales Distribution Product Marketing Customer Accounts Finance Operations and Inventory Vendors An Incremental Approach

11. ArchitectedEnterpriseFoundation Sales Distribution Product Marketing Customer Accounts Finance Operations and Inventory Vendors Enterprise Data Warehouse The Eventual Result

12. Data Mining Provides a means of extracting previously unknown, predictive information from the data warehouse Uses sophisticated, automated algorithms to discover hidden patterns, relationship among data Some Benefits: Market Segmentation Fraud Detection Market Basket Analysis Trend Analysis

13. Business Intelligence BI/Analytics software (suite): Used to collect, store, analyze and present sufficient and accurate information in a timely manner and in a usable form Includes OLAP, data mining, statistical analysis Has a positive impact on business strategy, and operations Addresses analysis paralysis?

14. Business Intelligence Enterprise BI Suites and Platforms

15. Other Trends Linking Web Applications to Organizational Databases Highly specialized database team - DBA, Data Administration Staff and Data Analysts Information Resource Management

16. Why learn about databases? Minimize disadvantages of traditional file environment Improve productivity on personal/professional fronts Without support and understanding of management at different levels, database efforts fail Budget vs. Cost Could be expensive in the long run Maintaining qualified DBA staff Creating Data Warehouse

17. Why learn about databases? Communicate effectively with DBA and his/her staff Data model should reflect key business processes and decision-making requirements Information Policy Which current trends in database are important for your unit/firm? Smooth transition for newly hired DBA staff Information Resource Management