Data Warehouse Practice

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1. 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.

2. 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

3. 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
Workflow Variables and Tasks
 Link Conditions
 Workflow variables
 Assignment task
 Decision Task
 Email Task
Summary of the Data warehouse project
 Description of project lifecycle
 Achievements Review



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