Data Modelling Training

(3) 3 Ratings

Course Schedule

30

JUL

Mon - Sat

07:30 PM - 10:00 PM ( IST )

06

AUG

Mon - Fri

11:00 AM - 02:00 PM ( IST )

11

AUG

Sat - Sun

05:30 AM - 06:30 AM ( IST )


Total Learners

874 Learners


LMS Access

365 days

Course duration

30 days


Support

24/7 support

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The Instructor for this course is from one of the Big5 Companies in the world.

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Modes of Training

Corporate Training

Live, Classroom Or Self Paced Training

Online Classroom

Attend our Instructor Led Online Virtual Classroom

Self Paced Training

Comprehensive Recorded Videos by Experts to learn at your own pace

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

☰ Details

Course Curriculum

Introduction to Logical Data Modeling

  • Definitions
  • Benefits of logical data modeling
  • Data modeling vs. physical database design
  • Roles involved in data modeling
  • Steps in the data modeling process
  • Example data model.

Entities

  • Identifying entities
  • Validating entities
  • Documenting "instances" of entities
  • Distinguishing entities from attributes
  • Naming entities
  • Starting an Entity/Relationship (E/R) diagram.

Relationships

  • Identifying significant relationships
  • Determining the "cardinality" or "degree" of a relationship
  • One-to-One
  • One-to-Many
  • Many-to-Many
  • Determining whether a relationship is optional or mandatory
  • Giving a relationship a name
  • Documenting the relationships in the E/R diagram
  • Walking people through an E/R diagram
  • Resolving Many-to-Many Relationships
  • Real-world examples of many-to-many relationships
  • Why many-to-many relationships are broken down into simpler relationships
  • Identifying "association" or "intersection" entities
  • Documenting the new relationships in the E/R diagram.

Attributes and Normalization

  • Defining and categorizing attributes
  • Domains and integrity rules
  • Unique identifiers/primary keys
  • Foreign keys
  • Occurrence population
  • Normalization: validating the placement of each attribute
  • Attribute does not repeat (first normal form)
  • Attribute is dependent on its entire UID (second normal form)
  • Attribute is dependent only on its UID (third normal form).

Subtypes and Supertypes

  • Identifying subtypes: real-world examples of subtypes and supertypes
  • Determining when entities are similar
  • UIDs
  • Attributes
  • One-to-one relationships
  • Creating subtypes and supertypes
  • "Type" entities
  • Using subtypes to apply fourth normal form
  • Establishing the relationships of the sub- and super-entities to other entities
  • Mutually exclusive vs. non-mutually exclusive subtypes
  • "Role" entities to handle complex subtypes.

Recursive Relationships

  • Real-world examples of recursive relationships
  • Discovering recursive relationships
  • Determining whether the relationships are optional or mandatory
  • Documenting the new relationships in the E/R diagram
  • Hierarchical vs. Network recursive relationships
  • "Structure" or "Bill of Materials" entities: fifth normal form.

Implementing a Relational Database

  • Relational database objects: tables, views, indexes, etc.
  • Mapping logical objects to physical objects
  • Denormalization
    • Why
    • How
    • Pros/Cons
  • Distributing databases
  • Referential integrity.

Course Description

What are objectives and learning outcomes of data modeling training?

  • Introduction to Logical Data Modeling, Entities and significant relationships.
  • Domains and integrity rules, subtypes and supertypes.
  • Understanding Relational database objects, Distributing databases and Referential integrity.
  • Learn about E/R diagram, Relational Database and Hierarchical vs. Network recursive relationships.
  • You should execute a real-time project based on the comprehensive course curriculum.
  • You will get to know the related jobs and job trends in the industry.

Who Should Attend this Training?

  • Systems analysts
  • business analysts
  • project managers
  • project coordinators
  • project analysts
  • team leaders
  • product managers 

What are the Pre-requisites for this Training?

  • As such, there are no prerequisites for learning Data Modeling. Some programming Skills is required.

FAQ

Do you have self paced training?

Yes, we offer self paced training

How do you provide training?

We offer three different modes of training. Instructor Led Live Training, Self Paced Training and Corporate Training

Do you offer any discounts?

Yes we offer discounts for group of 3 plus people.

Can I choose timings that suits my schedule?

Yes we are the only company where we work with students and offer flexible timings which fits your schedule

Who are the Instructors?

All our instructors are from MNC companies who have real time experience of more than 10 years.

Can I attend a demo session before joining?

Yes we offer a free demo session with the instructors. The trainer will answer all your queries and share the course agenda.

Course Reviews

Siva

Had a Great experience in Learning the course with LTB. Trainer was a Real-Time Expert and taught us with Real-Time Scenarios. Thank you.

Avanthika

Hi myself Avanthika, I really impressed with the experience in LTB. Our trainer is one of the best I have ever seen. He taught each and every concept in detailed manner. Thank you so much.

Shilpa

I also refer my friends to undergo Data Modelling Training at LTB …It’s a good environment to learn with the knowledgeable and experienced trainers … The way of explaining the concepts is very different. Thanks to LTB.