DATA MODELLING

Introduction

Data Modeling Training
Data modeling stands as a 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 set up and configures most complex data from various sources into an organized information flow that enables key personnel to take business informed decisions. The Data Modeling Training at Goldstone Inc stands at par with industry’s real-time scenarios.

Why Learn Data Modeling?

In the modern days’ businesses are dealing with large unstructured data to improve their business by predicting the sales, marketing in better ways, deriving new strategies all because of data available but the data is too huge and cannot be easily understood. So we designed this Data Modeling course in such a way that you can easily draw data flow representations from complex system designs to simple and efficient data flows and processes. You can re-design and create a blueprint for the design. Data Modeling Training gives you complete knowledge of designing the flowchart that represents the relation between data-oriented structures and identifies entity types.

Course Objectives
What you’ll learn in Data Modeling Training Course?
A practical guide to creating 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 of customizing pre-built data models.
Course curriculum designed from a 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 an 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
Subtypes Vs Supertypes
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, Snowflake
OLAP Conceptual, Feature and Functionality
Logical Overview of Data Mining, Data Preprocessing and Data Modeling