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          Oracle Data Warehouse 10g
          Oracle Data Warehouse 10g
          Oracle Data Warehouse 10g
          Software Version Oracle 10g
          Course Duration 4 Days
          Course Type Class Room and Instructor-Led On-Line (E-Learning) 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 Data Warehouse Consultants.
          Course Topics
          Data warehousing Overview
            Understanding Data Warehouse Builder
            Data Objects
            Data Definitions
            Designing ETL objects
            Designing Mappings
            Designing Process Flows
            Deploying Target Systems
            Role of Business Intelligence
            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
          ETL Process
            Introduction to ETL
            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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