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Data Warehousing: An Overview Katherine Watier December 3, 2001

Data Warehousing: An Overview Katherine Watier December 3, 2001. What is a Data warehouse?. It allows business to ask complex questions about data that is stored in separate systems. The business user can create reports and graphs to display this data

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Data Warehousing: An Overview Katherine Watier December 3, 2001

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  1. Data Warehousing: An OverviewKatherine WatierDecember 3, 2001 MGMT 257-01- Katherine Watier

  2. What is a Data warehouse? • It allows business to ask complex questions about data that is stored in separate systems. • The business user can create reports and graphs to display this data • The user can look at data summaries across time or other detailed attributes • It supports data mining which recognized patterns in the data and alerts managers to future trends. MGMT 257-01- Katherine Watier

  3. Benefits of Data Warehousing Benefit # 1: Users can ask questions like: “Why were sales up in the Pacific Region but not in the Mountain Region?” or “Why are we over budget” MGMT 257-01- Katherine Watier

  4. Benefits of Data Warehousing • Benefit #2: Using Data Mining, the system can recognize patterns within data and predict future behaviors based on current characteristics MGMT 257-01- Katherine Watier

  5. Benefits of Data Warehousing • Benefit # 3 Increased organizational knowledge- enhancing competitive advantage “The common factor which triggers investment in data warehousing appears to be competitive intensity.” Kelly . Data Warehousing: The Route to Mass Customization. 1994: 14 MGMT 257-01- Katherine Watier

  6. Data Warehouses Vs. Transactional Databases Transactional System • System that tracks real-time data • Large queries bog down performance of system • Separate from other data systems • Fast (often near instant) queries • Hundreds of users access the system at one time • Time stamped with time of event • Event oriented • Volatile • Limited size usually within one hardware system • Usually requires custom training to use • Difficult to scale & add features • Current (Real-Time) Data • Data often created from one source • Highly normalized Data Structure • Due to stable transaction definitions, database design is relatively stable MGMT 257-01- Katherine Watier

  7. Data Warehouses Vs. Transactional Databases Data Warehousing System • System that monitors trends and other patterns • Available for large queries without bogging down daily functions • Integrated • Queries can take hours to days to complete • Limited number of users • Time-stamped with period of time • Subject oriented & Non-volatile • Systems often large and require parallel hardware structures • Easily accessible to users with limited training • Easy to scale & add features • Data is usually 5-10 years old • Data input from multiple sources in a variety of formats. • Often de-normalized • Constantly changing business requirements; design needs to be adaptive MGMT 257-01- Katherine Watier

  8. What Does a Data Warehouse look like? End User Data Access Tools Data Warehouse Sources - Data mining - DSS - OLAP Integrated Data Operational Data Data Warehouse Highly Summarized Lightly Summarized Detail Level External Data Metadata An architected environment optimized for analytical and informational processing. MGMT 257-01- Katherine Watier

  9. Data warehouse Architecture The pieces: • Online Transactional Processing OLTP/legacy systems which provide the data • Transformation/propagation tools • Data warehouse database server • Metadata repository (data about the data) • Data marts for highly specified querying (usually for a department) • Analysis/end-user tools (OLAP) MGMT 257-01- Katherine Watier

  10. The Data Flow 1. The Source Data Data originates from a variety of sources: • Transaction system (registration application, accounting application, etc.) • Legacy systems • Websites • External Market Research Data MGMT 257-01- Katherine Watier

  11. The Data Flow 2. Data Integration &Transformation Data needs to be transformed into a universal format before being imported. The I&T layer focuses on: • Resolving key differences • Resequencing of the data • merging of the data • Summarizing the data • Creating data about the logic of the transformation that is stored in the metadata repository. MGMT 257-01- Katherine Watier

  12. The Data Flow 3. Metadata Repository Data about the data needs to be stored to: • Help users analyze the data • Maintain a history about how data was handled from its source to its storage MGMT 257-01- Katherine Watier

  13. “Star Schema” Database Design Customer Facts ---------- ---------- ---------- ---------- ---------- ---------- Time dimension Region dimension Customer dimension Product dimension Congress dimension Five database tables linked to provide information about Customers. MGMT 257-01- Katherine Watier

  14. Real Life Example of Star Schema MGMT 257-01- Katherine Watier

  15. Rules for Success in Building a Data Warehouse • Define the business problem before you start to build anything • Think architecture not databases • Begin small, grow incrementally • Develop one subject area first, deploy, maintain and expand for the enterprise • Make sure there is close collaboration between IT and the end-users MGMT 257-01- Katherine Watier

  16. References: IBM online. Retrieved from the World Wide Web October 23, 2001. http://www- 1.ibm.com/servers/eserver/iseries/db2/dataware.htm#header_4 Barquin, R. & Edelstein, H. 1997. Planning and Designing the Data Warehouse. Prentice Hall PTR, Upper Saddle River, NJ. Berson, A. & Smith, S. 1997. Data Warehousing, Data Minding, & OLAP. McGraw- Hill, New York, NY. Hammergren, T. 1998. Data Warehousing on the Internet: Accessing the Corporate Knowledge Base. International Thompson Computer Press: Boston, MA. Inmon, W.H., Imhoff, C., & Sousa, R. 2001. Corporate Information Factory. Wiley Computer Publishing: New York, NY. Kelly, Sean. 1994. Data Warehousing: The Route to Mass Customization. John Wiley & Sons: New York, NY. Kelly, S. 1997. Data Warehousing in Action. John Wiley & Sons, Ltd. New York: NY. Moeller, R.A. 2001. Distributed Data Warehousing Using Web Technology: How to Build a More Cost-Effective and Flexible Warehouse. AMACOM: New York, NY. Poe, Vidette. 1996. Building a Data Warehouse for Decision Support. Prentice Hall PTR: Upper Saddle River, NJ. Westerman, Paul. 2001. Data Warehousing: Using the Walmart Model. Morgan Kaufmann Publishers: San Francisco, CA. MGMT 257-01- Katherine Watier

  17. Barquin InternationalCorporate Intranet Project MGMT 257-01- Katherine Watier

  18. A little background… Barquin International was established in 1994 by Dr. Ramon C. Barquin. Dr. Barquin was the founder, and the first president of The Data Warehousing Institute.  BARQUIN’s mission: to assist enterprises in extracting business meaning from their data and developing competitive advantage through the use of data warehousing, data mining, knowledge management and other business intelligence disciplines. We offer the following services: MGMT 257-01- Katherine Watier

  19. Business Case for the Project Issue #1: • Barquin bids on a variety of projects and depending on the project’s focus we often need to hire consultants. • Over the past 4 years the company has accumulated over 250 resumes which need to be stored in such a way that we can search them by applicant location and skill set. MGMT 257-01- Katherine Watier

  20. Business Case for the Project Issue #2: • Company contact information which includes: • Consultant, corporate partner, and vendor addresses and phone numbers are stored in separate Outlook Contact lists or in the managers’ Palm Pilots. • Every time someone needs a phone number, they have to ask the other staff in the office if they have that phone number, which results in a wasting of staff time. MGMT 257-01- Katherine Watier

  21. Business Case for theProject Issue #3: • Proposal Writing: • When creating proposals for technical solutions, often we need to provide summaries of the functionality of various data warehousing products. • Currently, that information is re-created each time or stored in a staff’s personal file structure. MGMT 257-01- Katherine Watier

  22. The Solution The intranet developed will allow for the storage and querying of a variety of information including: • People that are related to Barquin • This includes: employees, applicants, consultants, etc. • Companies that interact with Barquin • Products that we use • Resumes from prospective employees/consultants MGMT 257-01- Katherine Watier

  23. Status of the Project Currently, most information can be added inserted, deleted and viewed for all 4 categories. MGMT 257-01- Katherine Watier

  24. What Still Needs to be Developed: -Cosmetics Various visual editing needs to be done. -Password issues The password needs to be hidden from view and every page needs to be checked for the password -Resume commenter The resume input form needs to be pre-populating the form with administrator's names MGMT 257-01- Katherine Watier

  25. What Didn’t Make it Past the Cutting Room Floor Originally intended to track: • The data warehousing classes we provide-who taught them, the materials they used, who took the classes. • The projects we have finished -what they were, who they were completed for, who was involved, the price of the contract, summary information 3. A pop-up survey for our Internet site asking the visitor knowledge management questions 4. Simple registration vehicle for our Internet site before allowing users to download our white papers. MGMT 257-01- Katherine Watier

  26. Questions? MGMT 257-01- Katherine Watier

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