KITS Online Training Institute provides best Data Modeling Online Training by our highly professional trainers. Data Modeling is often the first step in database design and object-oriented programming as the designers first create a conceptual model of how data items relate to each other. Data modeling involves a progression from conceptual model to logical model to physical schema. We are delighted to be one of the best leading IT online training with best experienced IT professionals and skilled resources. We have been offering courses to consultants, companies so that they can meet all the challenges in their respective technologies.

Highlights of Data Modeling Online training:-

*  Very in depth course material with Real Time Scenarios for each topic with its Solutions for Data Modeling Online Trainings.

*  We Also provide Case studies  for Data Modeling Online Training.

*  We do Schedule the sessions based upon your comfort by our Highly Qualified Trainers and Real time Experts.

*  We provide you with your recorded session for further Reference.

* We also provide Normal Track, Fast Track and Weekend Batches also for Data Modeling Online Training.

* We also provide Cost Effective and Flexible Payment Schemes.

Data Modeling Training Course Content

Data Modeling: An Overview

Data Model Defined

What Is a Data Model?

Why Data Modeling?

Who Performs Data Modeling?

Conceptual Data Modeling

Data Model Components

Data Modeling Steps

Data Model Quality

Significance of Data Model Quality

Data Model Characteristics

Ensuring Data Model Quality

Data System Development

Data System Development Life Cycle

Roles and Responsibilities

Modeling the Information Requirements

Applying Agile Modeling Principles

Data Modeling Approaches and Trends

Data Modeling Approaches

Modeling for Data Warehouse

Methods, Techniques, and Symbols

Data Modeling Approaches

Semantic Modeling

Relational Modeling

Entity-Relationship Modeling

Methods and Techniques


Anatomy of a Data Model

Data Model Composition

Models at Different Levels

Conceptual Model: Review Procedure

Conceptual Model: Identifying Components

Creation of Models

Entity Types

Specialization Generalization




Review of the Model Diagram

Logical Model: Overview

Model Components

Transformation Steps

Relational Model

Physical Model: Overview

Model Components

Transformation Steps

Entities in Detail

Entity Types or Object Sets

Comprehensive Definition

Identifying Entity Types

Generalization and Specialization

Why Generalize or Specialize?

Supertypes and Subtypes

Generalization Hierarchy

Recursive Structures

Conceptual and Physical

Modeling Time Dimension


Entity Validation Checklist



Attributes and Identifiers in Detail


Properties or Characteristics

Attributes as Data

Attribute Values

Names and Descriptions

Attribute Domains

Definition of a Domain

Domain Information

Attribute Values and Domains

Value Set



Null Values

Types of Attributes

Single-Valued and Multivalued Attributes

Simple and Composite Attributes

Attributes with Stored and Derived Values

Identifiers or Keys

Need for Identifiers

Definitions of Keys

Relationships in Detail



Relationship: Two-Sided

Relationship Sets

Double Relationships

Relationship Attributes

Degree of Relationships

Unary Relationship

Binary Relationship

Ternary Relationship

Quaternary Relationship

Structural Constraints

Cardinality Constraint

Participation Constraint


Entity Existence

Relationship Types

Identifying Relationship

Nonidentifying Relationship

Maximum and Minimum Cardinalities

Mandatory Conditions: Both Ends

Optional Condition: One End

Optional Condition: Other End

Optional Conditions: Both Ends

Special Cases



Access Pathways

Design Issues

Relationship or Entity Type?

Ternary Relationship or Aggregation?

Binary or N-ary Relationship?

One-to-One Relationships

One-to-Many Relationships

Circular Structures

Redundant Relationships

Multiple Relationships

Relationship Validation Checklist



Data Normalization

Informal Design

Forming Relations from Requirements

Potential Problems

Update Anomaly

Deletion Anomaly

Addition Anomaly

Normalization Methodology

Strengths of the Method

Application of the Method

Normalization Steps

Fundamental Normal Forms

First Normal Form

Second Normal Form

Third Normal Form

Boyce-Codd Normal Form

Higher Normal Forms

Fourth Normal Form

Fifth Normal Form

Domain-Key Normal Form

Normalization Summary

Review of the Steps

Normalization as Verification

Modeling for Data warehouse

Decision-Support Systems

Need for Strategic Information

History of Decision-Support Systems

Operational Versus Informational Systems

System Types and Modeling Methods

Data Warehouse

Data Warehouse Defined

Major Components

Data Warehousing Applications

Modeling: Special Requirements

Dimensional Modeling

Dimensional Modeling Basics

STAR Schema

Snowflake Schema

Families of STARS

Transition to Logical Model

OLAP Systems

Features and Functions of OLAP

Dimensional Analysis


OLAP Implementation Approaches

Data Modeling for OLAP

Data Mining Systems

Basic Concepts

Data Mining Techniques

Data Preparation and Modeling

Data Preprocessing

Data Modeling

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