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

2 Data Warehousing Lab. DW Chapter 1 - Warehouse: What is it, Who needs it, and Why? n n 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. n n We will answer the following questions. p What is business intelligence? p What are the business and technical goals of business intelligence? p What is data warehousing? p What are the business drivers of data warehousing? p What are the technical drivers of data warehousing?

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

4 Data Warehousing Lab. DW The Goal: Business Intelligence n The real goal of reporting systems is decision support – business intelligence n 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 Data Warehousing Lab. DW An automatic Teller Machine(ATM)- For Data n Figure 1.2 shows how IS has gone from being the conduit to being the builder of the conduit

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

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

8 Data Warehousing Lab. DW Integrated n Figure 1.5 illustrates this difficulty – the marriage of different coding schemes into one for the warehouse data.

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

10 Data Warehousing Lab. DW Time Variant n Time is a very important component of reporting and, thus, of data warehouses.

11 Data Warehousing Lab. DW Business Intelligence Differs from Transaction Processing n Difference between business intelligence computing and operational computing Operational system Business intelligence system SizeSmall pieces of informationHuge blocks of information UpdateFrequently be updated in real time Almost never needs to be updated in real time Data inputRapid inputEnter no data, nonvolatile Response time Need immediate responseDon’t need such blazing response times Usage pattern PredictableNot stable Database design complexEasy for users

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

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

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

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

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