Database – Part 3 Dr. V.T. Raja Oregon State University External References/Sources: Data Warehousing – Mr. Sakthi Angappamudali

Database – Part 3 - Outline Some database trends (past and recent) Why learn about databases?

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

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

Other Trends Object Oriented Databases Hypermedia Databases Linking Web Applications to Organizational Databases OLTP, OLAP, DW, DM, BI and Analytics

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

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

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 gigabytes - petabytes of data Run on very powerful computers Expensive

Design Mapping Design Mapping OLTP Systems Functional IS External Data OLTP - Raw Detail No/Minimal History DW-Integ. 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

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)

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

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

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

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?

Why learn about databases? Minimize disadvantages of traditional file environment Improve productivity on personal/professional fronts Budget vs. Cost (DB could be expensive in the long run) Maintaining qualified DBA staff Creating Data Warehouse Investing in BI Software SOX Compliance

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 Without support and understanding of management at different levels, database efforts fail