Data Modeling

Data Modeling

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    Introduction

    Keen Technologies is your best online training partner offering an entire range of IT Professional courses and imparting training at a learner’s pace. Data modeling stands as foundation plan for users to communicate information requirements about various business processes as well as for developers to consider those requirements while constructing an effective physical database. Data Modeling is today’s most essential data management tool for organizations to setup and configure most complex data from various sources into an organized information flow that enables key personnel take business informed decisions. The Data Modeling course at Keen Technologies stands at par with industry’s real time scenarios. Take a quick look at the Course summary below.

    COURSE SUMMARY

    Course Name Data Modeling
    Course Contents Fundamentals of Data Modeling
    Course Duration 30 Hours with Flexible timings
    Course Delivery Instructor Led-Live Online Training
    Course Eligibility Any Graduate
    Ideal For Fresher, aspiring  job seekers in the field of BO
    Next Batch Please visit the schedule section

    Course Objectives

    HIGHLIGHTS OF DATA MODELING

    • Practical guide to create Data Model for Business Intelligence and Data Warehouse applications
    • Detailed Coverage of Data warehouse , Database and Business Intelligence conception
    • SQL framework in relation with Data Modeling
    • Knowledge on customizing pre built data models.
    • Course curriculum designed from job standpoint.

    CORE BENEFITS OF LEARNING DATA MODELING

    The growing needs of global data management are challenging organizations to design well-organized data models in place or preen the existing data models to support the dynamic business requirements, thus creating wide opportunities for organizations as well as professionals for innovating critical business objects. Data Modeling is therefore a sought after specialization.

    KEY FOCUS AREA

    Data Modeling Key Concepts, Layer Architecture, Relational Data Models, Schemas, Methods and Attributes, Design data Model with definite user group information requirements.

    Course Curriculum

    Data Modeling is vital to design data life cycle of organization’s business portfolios. An efficient data model organizes business relevant objects, their relationships, integrates with other applications to provide accurate, reliable and secure information to key users. This course is designed to help aspirants understand the essence of data modeling while building effective business models.

    CONTENTS :

    NEED FOR DATA MODELING

    • Introducing the Data Modeling concept with real time scope and benefits
    • Role and Responsibilities of industry wide Data Modeling Experts
    • Business requirements analysis in data modeling
    • Types of Data Models and Databases
    • Data Model Components , quality ,characteristics , Trends
    • Overview of Development Life Cycle

    DATA MODELING NITTY-GRITTY

    • Data Models at various levels
    • Conceptual model creation
    • Attributes Vs Entities
    • Identifiers
    • Relationships
    • Specialization and generalization of Entity
    • Model Diagrams
    • Logical Data Model design : Step by step Transition
    • Physical Data Model : Step by Step Transition

    ANATOMY

    • Definition of Entity , Types
    • Entity Object Sets , Categorization
    • Sub types Vs Super types
    • Conceptual Vs Physical
    • Entity Validation
    • Recursive Structures
    • Complete set of correct entities
    • Modeling time data

    ATTRIBUTE AND IDENTIFIER

    • Definition, features ,value set, types , domain
    • Defining attribute in data model
    • Simple Vs Composite Attribute
    • Concept of Stored and derived values
    • Purpose of Identifier
    • Define and Set key for Identifier

    RELATIONSHIPS

    • Definition, Types , Degree of dependency
    • Constraints : Structural , cardinal & Participation
    • Relationship Attributes
    • Identifying Relationship
    • Optional Conditions , Special Cases , Design Issues
    • Aggregation , Gerund , Access Pathway
    • Relationship Models with Multiple Concept: One – One , One –Many
    • Structures in Relationship
    • Concept of Redundancy in Relationships
    • Relationship Checklist for completeness and correctness

    DATA MODELING – NORMALIZATION

    • Map Relations from requirements
    • Figure out possible errors and resolution
    • Normalization Definition , Purpose and Methodology
    • Detailed Coverage of Normalization Steps
    • Normal Forms and evolution
    • BCNF
    • Domain Key Normal Form
    • Normalization synopsis

    DESIGN DATA WAREHOUSE WITH DATA MODELING

    • Data Warehouse fundamentals
    • Information Grouping : Strategic Vs Operational
    • Decision Support Systems and types
    • Dimensional Modeling , Analysis
    • Schema : Star , Snow flake
    • OLAP Conceptual , Feature and Functionality
    • Logical Overview of Data Mining , Data Preprocessing and Data Modeling

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        Course Features

        Live Instructor-led Classes

        This isn't canned learning. Its dynamic, its interactive, its effective

        Expert Educators

        Only the best or they're out. We are constantly evaluating our trainers

        24&7 Support

        We never sleep. Need something answered at 3 am? No Problem

        Flexible Schedule

        You don't learn as per our calendar. We work according to yours.

        Customized Training's

        The most part self-managed and adaptable to suit a person's particular adapting technology needs

        Priority Based Training's

        Real-time Scenario based Assignments and Case Studies

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