Logical Data Model :

In my previous article I have given the basic idea about the Dimensional data modeling.In this article i would like to explain the concept of Logical Data Model with real life examples. I want to focus on some important examples of Logical Data Model. The Logical data modeling  is nothing but the logical representation of the database to achieve the specific purpose. There are so many different concepts that user needs to understand regarding Logical Data Model. The logical data model always represents the physical data architecture of the database. The logical data modeling gives us information about all the entities with relationship between those entities present in database.

Logical Data Model is nothing but the detailed structure of database.

Different Features of Logical Data Modeling  :

This concept is mainly used in Business processes which will capture the information about organization.The concept is used in reporting purpose and development of RPD purpose in OBIEE like Business Intelligence applications.In this section i would like to explain about the different features of Logical Data Modeling.

1.Include all Entities and Relationships :

The Logical Data Model Should include all entities in specified database with its relationship.

2.Primary Key :

User needs to define the primary key for each entity specified in the model.

3.Foreign Key :

User needs to define the foreign key to specify the relationship between the two or more entities.

4.Specify All Attributes :

User needs to specify all attributes for Each and every entity using in the data model.

5.Normalization :

User needs to specify the database normalization and needs to use the normalization.

These are above some most important features of data modeling.Logical data modeling is not providing the information about structure to be implemented.It will give you information related to the logical structure of the database.

Why Logical Data Model?

Everyone have question in mind that Why user needs to convert the physical data model in to logical data model.In this section i will explain the different reasons for using the Logical data model.

1.Complexity of Data :

There are so many physical data structure which are really very complex to handle.When user wants to handle the complex relationship between data entities the Data model is very useful.

2.Understanding the Business requirements :

The logical data model is very useful for understanding different business requirements in easy way.

3.Helps in Database Design :

The Logical data modeling helps in foundation of complex database design.

4. Resusability :

The Logical data modeling provides the way of reusing the data in proper way.

5.Decreasing Development and maintenance cost :

Its better to work on simple Logical model rather than the complex physical data model.

These are some most important reasons of using the Logical data modeling techniques.The basic reason for using the logical data modeling is to avoid the complexity in physical data structure.The physical data structure will make more complex query than logical

data structure if you practically test it.

How to design Logical Data Model :

In this section i would like to give you example of Logical data modeling techniques with some of the important steps.The physical data model is more detailed representation of the database. Our purpose is to represent the physical data model with logical way and in normalized form.The Logical data model in mainly in Star schema sometimes in hybrid schema as well.

Step 1 : Specify the primary key 

The first step of creating the logical data modeling is specify the primary key for every entity.

Step 2 : Find the relationship between different entities

The second step is to specify the relationship between the different entities.

Step 3 :Find out all the attributes according to business need

The third step is find out all the attributes according to business need

Step 4 :Snowflakes to Star Schema

User needs to convert the design of snowflakes to star.User needs to convert the many to many relationship from one to many relationship.

Step 5 :Normalization of database

The attributes needs to convert in to normalized database.The Logical data model is fourth normal form.

Conceptual Data Model vs Logical Data Modeling :

In this section i would like to explain the Conceptual Data Model vs Logical data model.

These are some most important key-points of logical data modeling and its techniques.I hope this article is useful for you.If you like this article or if you have any questions or concerns with the same kindly comment it in to comment section.