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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

Oracle 8i Data Warehousing(chapter 1, 2)

Data Warehousing Lab.

석사1학기 HyunSuk Jung

chapter 1 warehouse what is it who needs it and why
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?
problems with the current reporting architecture
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?

the goal business intelligence
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.
an automatic teller machine atm for data
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
so what s data warehouse
So, What’s Data Warehouse?
  • Inmon describes the warehouse as

“subject-oriented, integrated, nonvolatile, time-variant collection of data in support of management decisions.”

subject oriented
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?
integrated
Integrated
  • Figure 1.5 illustrates this difficulty – the marriage of different coding schemes into one for the warehouse data.
nonvolatile
Nonvolatile
  • Warehouse is read-only. Users can’t write back.
  • Figure 1.6 illustrates this fundamental difference between OLTP and the data warehouse.
time variant
Time Variant
  • Time is a very important component of reporting and, thus, of data warehouses.
business intelligence differs from transaction processing
Business Intelligence Differs from Transaction Processing
  • Difference between business intelligence computing and operational computing
why oracle8i for data warehousing
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
chapter 2 things to consider
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

data mart or data warehouse
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.
data warehouse differences
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?
why oracle for data warehousing
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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