1. Data Management for Decision Support Session - 1 Prof. Bharat Bhasker

2. Course Outline Assignments 50% –Surprises! –HW – Papers/ Cases (10 points) Final Exam50% What’s Expected? –Multiple Books ( DBMS, Data Warehousing, Computer Architecture) –Research Papers ( ToDS, Computing Surveys)

3. Productivity Paradox In 1994, US $464 Billion were spent on IT, but ROI didn’t measure up.==> –Automation of Clerical tasks –Improving efficiency of existing processes –Gathering & Collection of Data went up, but no significant changes in deployment of the technology to extract value

4. Potential for ROI Management of data offers potential ROI Ability to focus on business processes, perform complete financial analysis and make decisions based on understanding of the entire system Ability to organize data for both macro and micro level analysis Dynamic drill down through the reports generated via EIS Quick responses to ad-hoc queries for testing hypothesis Correlate current and historical data IDC survey showed average 3 year return reached 400% for data warehousing!!

5. Why Manage the Accumulated data Information needs of Knowledge workers, Strategic planners, Customers & Vendors can be met from the accumulated data. Business Perspective==> –Quick and correct decision making using all available data –Users are domain expert, not software pros –Data double every 18 months, effects response time and comprehension –Business Intelligence the new emerging tool

6. Why Manage the Accumulated data Technology Perspective –Price of processing power in MIPS declines, while power of microprocessor double every 18 months. –The prices of digital storage continues to drop –The environment is heterogeneous is terms of H/W and S/W –Legacy systems can be integrated with new applications –N/W b/w is increasing, cost is declining

7. Introduction- Shifting Paradigm Computing Paradigm UsersNetworksComputers

8. Introduction- Shifting Paradigm Business Paradigm Legacy Enterprise Manual Back office Manual front office Automated Enterprise Back office Automation Front office Automation New Enterprise BPR Led, Paperless Office, Fully networked, distributed, & Knowledge enabled Proprietary Systems on Mainframes Open Systems, C/S, Distributed Computers

9. Problem: Heterogeneous Information Sources “Heterogeneities are everywhere” p Different interfaces p Different data representations p Duplicate and inconsistent information Personal Databases Digital Libraries Scientific Databases World Wide Web

10. Problem: Data Management in Large Enterprises Vertical fragmentation of informational systems (vertical stove pipes) Result of application (user)-driven development of operational systems Sales AdministrationFinanceManufacturing... Sales Planning Stock Mngmt... Suppliers... Debt Mngmt Num. Control... Inventory

11. Goal: Unified Access to Data Integration System Collects and combines information Provides integrated view, uniform user interface Supports sharing World Wide Web Digital LibrariesScientific Databases Personal Databases

12. The Traditional Research Approach Source... Integration System... Metadata Clients Wrapper Query-driven (lazy, on-demand)

13. Disadvantages of Query-Driven Approach Delay in query processing –Slow or unavailable information sources –Complex filtering and integration Inefficient and potentially expensive for frequent queries Competes with local processing at sources Hasn’t caught on in industry

14. The Warehousing Approach DataWarehouse Clients Source... Extractor/ Monitor Integration System... Metadata Extractor/ Monitor Extractor/ Monitor Information integrated in advance Stored in wh for direct querying and analysis

15. Advantages of Warehousing Approach High query performance –But not necessarily most current information Doesn’t interfere with local processing at sources –Complex queries at warehouse –OLTP at information sources Information copied at warehouse –Can modify, annotate, summarize, restructure, etc. –Can store historical information –Security, no auditing Has caught on in industry

16. Not Either-Or Decision Query-driven approach still better for –Rapidly changing information –Rapidly changing information sources –Truly vast amounts of data from large numbers of sources –Clients with unpredictable needs

17. What is a Data Warehouse? A Practitioners Viewpoint “A data warehouse is simply a single, complete, and consistent store of data obtained from a variety of sources and made available to end users in a way they can understand and use it in a business context.” -- Barry Devlin, IBM Consultant