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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?


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


  • 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.