DATA MODELING ONLINE TRAINING

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.

Data Modeling Training Course Content

Why Data warehousing

OLTP VS OLAP

Data Warehousing architecture

Normalization

  • 1st Normal form
  • 2nd  Normal form
  • 3rd  Normal form   with example

Conceptual Data Modeling

  • Discovering entities
  • Defining entities

Logical Data Modeling

  • Importance of logical data modeling in requirements
  • When to use logical data models
  • Elements of a logical data model
  • Super type and Sub types

Physical Data Modeling

  • Importance of physical data modeling in requirements
  • Elements of a physical data model
  • Difference between logical and physical data model

Identifying Relationships

  • One-to-one
  • One-to-many
  • Many-to-many
  • How to Resolve Many-to-many relationships

Identifying Attributes

  • Discover attributes for the subject area
  • Assign attributes to the appropriate entity
  • Name attributes using established naming conventions
  • Documenting attributes

 

Dimensional Modeling

What is Dimensional Modeling?

Why Dimensional modeling

Data warehouse vs Data Mart

Star schema vs Snow Flake

Fact

What is Fact

Fact types

Dimension

What is Dimensions?

Dimension types

SCD Type- 1

SCD Type-2

SCD Type- 3

Junk Dimension

Role Playing Dimension

Confirmed Dimension

Erwin

Entity

Attribute

Creating logical Model

Creating Physical Model

Domain

Subject Area

Forward Engg

Reverse Engg

Complete compare

SQL Server:

Basics to  till joins

Some interview questions

Note: Based on student requirement course content can be altered

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.

What is Data Modelling?

Data modeling is the process of creating a data model for the data to be stored in a Database. This data model is a conceptual representation of

  • Data objects
  • The associations between different data objects
  • The rules.

Data modeling helps in the visual representation of data and enforces business rules, regulatory compliances, and government policies on the data. Data Models ensure consistency in naming conventions, default values, semantics, security while ensuring quality of the data.

Types of Data Models

There are mainly three different types of data models:

  1. Conceptual: This Data Model defines WHAT the system contains. This model is typically created by Business stakeholders and Data Architects. The purpose is to organize, scope and define business concepts and rules.
  2. Logical: Defines HOW the system should be implemented regardless of the DBMS. This model is typically created by Data Architects and Business Analysts. The purpose is to developed technical map of rules and data structures.
  3. Physical: This Data Model describes HOW the system will be implemented using a specific DBMS system. This model is typically created by DBA and developers. The purpose is actual implementation of the database.

Conceptual Model

The main aim of this model is to establish the entities, their attributes, and their relationships. In this Data modeling level, there is hardly any detail available of the actual Database structure.

The 3 basic tenants of Data Model are

Entity: A real-world thing

Attribute: Characteristics or properties of an entity

Relationship: Dependency or association between two entities

For example:

  • Customer and Product are two entities. Customer number and name are attributes of the Customer entity
  • Product name and price are attributes of product entity
  • Sale is the relationship between the customer and product

Characteristics of a conceptual data model

  • Offers Organisation-wide coverage of the business concepts.
  • This type of Data Models are designed and developed for a business audience.
  • The conceptual model is developed independently of hardware specifications like data storage capacity, location or software specifications like DBMS vendor and technology. The focus is to represent data as a user will see it in the “real world.”

Conceptual data models known as Domain models create a common vocabulary for all stakeholders by establishing basic concepts and scope.

Logical Data Model

Logical data models add further information to the conceptual model elements. It defines the structure of the data elements and set the relationships between them.

The advantage of the Logical data model is to provide a foundation to form the base for the Physical model. However, the modeling structure remains generic.

At this Data Modeling level, no primary or secondary key is defined. At this Data modeling level, you need to verify and adjust the connector details that were set earlier for relationships.

Characteristics of a Logical data model

  • Describes data needs for a single project but could integrate with other logical data models based on the scope of the project.
  • Designed and developed independently from the DBMS.
  • Data attributes will have datatypes with exact precisions and length.
  • Normalization processes to the model is applied typically till 3NF.

Physical Data Model

A Physical Data Model describes the database specific implementation of the data model. It offers an abstraction of the database and helps generate schema. This is because of the richness of meta-data offered by a Physical Data Model.

This type of Data model also helps to visualize database structure. It helps to model database columns keys, constraints, indexes, triggers, and other RDBMS features.

Characteristics of a physical data model:

  • The physical data model describes data need for a single project or application though it maybe integrated with other physical data models based on project scope.
  • Data Model contains relationships between tables that which addresses cardinality and nullability of the relationships.
  • Developed for a specific version of a DBMS, location, data storage or technology to be used in the project.
  • Columns should have exact datatypes, lengths assigned and default values.
  • Primary and Foreign keys, views, indexes, access profiles, and authorizations, etc. are defined.

Advantages and Disadvantages of Data Model:

Advantages of Data model:

  • The main goal of a designing data model is to make certain that data objects offered by the functional team are represented accurately.
  • The data model should be detailed enough to be used for building the physical database.
  • The information in the data model can be used for defining the relationship between tables, primary and foreign keys, and stored procedures.
  • Data Model helps business to communicate the within and across organizations.
  • Data model helps to documents data mappings in ETL process
  • Help to recognize correct sources of data to populate the model

Disadvantages of Data model:

  • To developer Data model one should know physical data stored characteristics.
  • This is a navigational system produces complex application development, management. Thus, it requires a knowledge of the biographical truth.
  • Even smaller change made in structure require modification in the entire application.
  • There is no set data manipulation language in DBMS.

What You’ll Learn In This Data Modeling Course?

  • How logical data models relate to requirements
  • Identifying entities and attributes
  • Determining relationships and business rules
  • Data integrity through normalization
  • Learn to create use data models.

 Prerequisites to Learn Data Modeling?

  • Business Analysis Essentials
  • Requirements Development, Documentation, and Management
  • Use Case Modeling

Scheduling Demo With Trainer:

If you would like to take the online demo for Data Modeling trainer can you please make an inquiry or fill the form for demo registration, one of our executives will arrange a meeting with the expert trainer.

Course Finished Certificate :

After finish, the course we provide Data Modeling course finished certificate of kits technologies looks like

AWS online training

 

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