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Oracle 8i Data Warehousing (chapter 1, 2)

Oracle 8i Data Warehousing (chapter 1, 2). Data Warehousing Lab. 석사1학기 HyunSuk Jung. Chapter 1 - Warehouse: What is it, Who needs it, and Why?.

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Oracle 8i Data Warehousing (chapter 1, 2)

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  1. Oracle 8i Data Warehousing(chapter 1, 2) Data Warehousing Lab. 석사1학기 HyunSuk Jung

  2. Chapter 1 - Warehouse: What is it, Who needs it, and Why? • This chapter will help you what users require from a business intelligence system(BIS) and why a data warehouse is often necessary to satisfy these demands. • We will answer the following questions. • What is business intelligence? • What are the business and technical goals of business intelligence? • What is data warehousing? • What are the business drivers of data warehousing? • What are the technical drivers of data warehousing?

  3. Problems with the Current Reporting Architecture • Accessibility : Can I get to my information when I need it? • Timeliness : How long after transactions occur do I get my information? • Format : What kind of reports can I get? • Integrity : Can I believe the data I get? Is it accurate?

  4. The Goal: Business Intelligence • The real goal of reporting systems is decision support – business intelligence • Business intelligence system is a system that give users access to their data and allows them to analyze and format the data as needed.

  5. An automatic Teller Machine(ATM)- For Data • Figure 1.2 shows how IS has gone from being the conduit to being the builder of the conduit

  6. So, What’s Data Warehouse? • Inmon describes the warehouse as “subject-oriented, integrated, nonvolatile, time-variant collection of data in support of management decisions.”

  7. Subject Oriented • Subject-oriented information is key in situations like this.(as manager) • How could they allocate sales resources? • How could they make production plans? • How could they justify their huge bonuses?

  8. Integrated • Figure 1.5 illustrates this difficulty – the marriage of different coding schemes into one for the warehouse data.

  9. Nonvolatile • Warehouse is read-only. Users can’t write back. • Figure 1.6 illustrates this fundamental difference between OLTP and the data warehouse.

  10. Time Variant • Time is a very important component of reporting and, thus, of data warehouses.

  11. Business Intelligence Differs from Transaction Processing • Difference between business intelligence computing and operational computing

  12. Why Oracle8i for Data Warehousing? • Oracle8i – Relational Database • Oracle Reports & PL/SQL – Development Tools • Oracle Warehouse Builder(OWB) – ETL • Express – Multidimensional Database Engine • Discoverer – Relational OLAP Query Tool • Oracle Data Mining Suite

  13. Chapter 2 – Things to Consider • Be Pragmatic • Articles and Books contain Opinions, Not Facts • Buyer Beware! • Start with business Requirements – Not Technology : data warehousing is not about technology. data warehousing is about solving business problems

  14. Data Mart or Data Warehouse? • Data mart vs Data Warehouse • Data warehouse is a “broad” data store, contains a number of subject areas. • Data mart focuses on a more narrow part of business, covers a single subject area. • Build small, but think big. • For example, the telecommunications department needs to analyze long-distance usage on a monthly basis. It will build its mart using two data sources: • It will gather data from the corporate data warehouse about every employee, their phone number, and their departments. • It will gather data from its long-distance provider about the long-distance usage from each phone.

  15. Data Warehouse Differences • A Developer’s Perspective • Mindset • data-capture data distribution • “How quickly can I insert this row in the database?” “How can I deliver results to a query that summarizes 10 million rows in a reasonable amount of time” • Denormalization • Predicting the work that a user will request. • “Predoing” it in a batch job so that the system doesn’t have to do it when the user submits his or her query. • The User’s Perspective • Unreliable data? • Poor response time? • Complex user interfaces?

  16. Why Oracle for Data Warehousing? • Total Solutions • OLAP and Server Access • Parallel Query Option(PQO) : to provide for faster query throughput. • Cross-Platform accessibility : Oracle Open Gateway technology • Data Acquisition and Transformation : for moving and transforming data from source systems and it to the data warehouse or data mart.

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