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    Technical Courses
    Oracle Data Warehouse 10g
    Software Version Oracle 10g
    Course Duration 3 days or 24 Hours Approx
    Course Type Class Room and On-Line (E-Learning) Instructor-Led Hands-On Training
    Course Overview

    This course provides complete overview of designing, building and maintaining data warehouse. This course also covers warehouse technologies, data warehouse and business intelligence concepts, features of 10g database, implementation templates, Analytical workspace manager and Oracle Warehouse Builder.

    Intended Audience for this course This course is designed for those who have technical background, knowledge with any computer language, Java, J2EE, XML, .NET Developers, Business Intelligence Developer, Data warehouse Administrator, Data Modelers, End Users, ERP Developers, DBAs, Functional Consultants, IT management and Staff, Business Analysts, Data Warehouse Analyst, Technical Consultants, Students and also those who want to become Oracle Applications Consultants.
    Course Topics
    Data warehousing Overview
    • Understanding Data Warehouse Builder
    • Data Objects
    • Data Definitions
    • Designing ETL objects
    • Designing Mappings
    • Transformations
    • Designing Process Flows
    • Deploying Target Systems
    • Role of Business Intelligence
    • Components
    • OLTP and OLAP Overview
    • Data Warehouse definitions
    • Data Marts
    • Development Approach
    • Common Terminology of Data Warehouse
    • Modeling Overview
    • Data Structures
    • Logical and Dimensional Modeling
    • Physical Modeling Overview
    • Partitioning Methods
    • Sizing Techniques
    • Security
    ETL Process
    • Introduction to ETL
    • Tasks
    • Data Sources
    • Issues and Design Options
    • ETL tools and Processes
    • Transforming Data
    • Loading Data
    Warehouse Data
    • Methods for capturing data
    • Capture and Refresh Mechanisms
    • Purging and Archiving Data
    • Tasks and Publishing Data
    • Controlling Access
    • Automating Processes
    OLAP and Data Mining
    • Introduction to OLAP
    • Data Mining Definitions
    • Analytical Processing
    • OALP and RDBMS integration
    Data Warehouse Implementation
    • Implementation requirements
    • Project Management Plan
    • Repository, Technical Architecture
    • Post Implementation and change management



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