Data Warehouse实战班


Course Introduction

This Project oriented Co-op course provides the experience to design and build Oracle Data Warehouse using most popular ETL tools Informatica, A real Data Warehousing Project guides you through the process of planning, designing, building and developing an integrated Oracle Data Warehouse / Data Mart. The most important point is you will gain Real Project experience working with Oracle Data Warehouse, Erwin, Informatica.

Your will learn How to:

  • Plan, design and build comprehensive Oracle Data Warehousing & BI project
  • Implement logical and physical Data Model for Oracle Data Warehouse / Data Mart using Erwin.
  • Develop Star Schema, Data warehouse summary table by using Materialized Views
  • Design ETL process, implement OLTP to OLAP source to target mapping process
  • Extract, transform and load (ETL) data into data warehouse
  • Design complex mapping process from data source to target
  • Perform Informatica Administrator and Developer tasks including install, configure and develop the ETL solution using the most important ETL software Informatica

Who should attend:

This course valuable for Oracle Developer / Database & Warehouse Design / ETL Developer / Database modeler, System Analyst, System Engineers, Consultants and others involved in building Oracle applications.

1. Objective

Upon completion of the course, participants should be able to:

  • Plan, Design and Build real Oracle Data warehouse project
  • Understand with Data Warehouse development life cycle, include define business requirement, system analysis, system design, construction and deployment.
  • Develop a multidimensional data model and generating Oracle database structure using Erwin
  • Gain Data Warehouse experience in Data Architecture, Data Modeling and logical and physical Database design
  • Perform Extracting, transforming and loading (ETL) data to Data Warehouse using Informatica

2. Course Content


  • Data Warehouse Architectures
  • Introduction of Informatica
  • Introduction of the data warehousing Co-op project

Data Warehouse Project Plan

  • Phase One – Vision
    • Vision Goals
    • Key Vision Deliverables
    • Vision Flow
  • Phase Two – Discovery
    • Discovery Goals
    • Key Discovery Deliverables
    • Discovery Flow
  • Phase Three – Architecture
    • Architecture Goal
    • Key Architecture Deliverables
    • Architecture Flow
  • Phase Four – Construction
    • Construction Goal
    • Key Construction Deliverables
    • Construction Flow
  • Phase Five – Implementation
    • Implementation Goal
    • Key Construction Deliverables
    • Construction Flow
  • Phase Six – Audit and Iteration
    • Audit and Iteration Goals
    • Key Audit and Iteration Deliverables
    • Audit and Iteration Flow

Define Data Warehouse Project Requirements

  • Interview process
  • Developing analytic themes
  • Linking themes to business process
  • Developing the data warehouse bus matrix
  • Prioritizing business processes

Data Warehouse / Data Mart Modeling

  • Design star schemas
  • Star schema benefits
  • Implementing database portioning
  • Dimensional vs. traditional approaches
  • Data Mart vs. Data warehouse
  • Define the metadata and metadata model sample

Creating the Logical Model

  • Develop the logical Data Model
  • Building Logical Relationships
  • Organizing and Enhancing the logical data model
  • Reviewing the logical data model
  • Delivering the logical data model
  • Advanced features for logical model

Creating the Physical Model

  • Develop the physical model
  • Build the physical model in Erwin
  • Build physical relationships
  • Review the physical data model
  • Delivery the physical data model
  • Default values and Validation rule
  • Tables / Columns
  • Views / Materialized Views / Temporary Tables
  • PK / FK / UK & Indexes
  • Script Generate procedure

ETL fundamental

  • Design ETL architecture
  • Design ETL metadata repository
  • Design ETL process
  • Document ETL process

Building Data Warehouse Using Informatica

  • Informatica architecture
  • Informatica connectivity
  • Informatica Clint tools
  • Informatica workflow

Informatica Designer

  • Source Analyzer
  • Warehouse Designer
  • Transformation Developer
  • Mapplet Designer
  • Mapping Designer

Informatica Sever Manager

  • Workflow
  • Configure Server
  • Create a Session
  • Run a Session
  • Monitor a session
  • Check Log

Repository Manager

  • Metadata Repository
  • Security Management
  • User Management
  • Permission

Advanced Mapping process design

  • Sorter Transformation
  • Aggregator Transformation
  • Active and Passive Transformations
  • Data Concatenation
  • Router, update Strategy and Overrides
  • Router Transformation
  • Update Strategy Transformation
  • Expression Default Values
  • Source Qualifier Override
  • Target Override
  • Session Task Mapping Overrides
  • Dynamic Lookup and Error Logging
  • Dynamic Lookup
  • Error Logging

Data Warehouse loading

  • Dimension table loading
  • Implementation of slowly change dimension
  • Fact table loading
  • Lookup all surrogate keys


  • Debugging Mappings
  • Parameters and Variables


  • Mapping Input Transformation
  • Mapping Output Transformation

Summary of the Data warehouse project

  • Description of project lifecycle
  • Achievements Review

Workflow Variables and Tasks

  • Link Conditions
  • Workflow variables
  • Assignment task
  • Decision Task
  • Email Task
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负责人:Kevin Wang
联系方式:416-665-1888 Ext:1
微信号:mariasunvic12 mariasunvic12