What is Difference between E-R Modeling and Dimentional Modeling.

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  • Mar 11th, 2006

Basic diff is E-R modeling will have logical and physical model. Dimensional model will have only physical model.

E-R modeling is used for normalizing the OLTP database design.

Dimensional modeling is used for de-normalizing the ROLAP/MOLAP design.

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  • May 13th, 2006

Adding to the point:

E-R modelling revovles around the Entities and their relationships to capture the overall process of the system.

Dimensional model/Muti-Dimensinal Modelling revolves around Dimensions(point of analysis) for decison making and not to capture the process.

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  • Jun 8th, 2006

hi everybody,In ER modeling the data is in normalised form. So more number of Joins, which may adversly affect the system performnace.Whereas in Dimensional Modelling the data is denormalised, so less number of joins, by which system performance will improve.bye.


  • Sep 1st, 2006

hi srinu

      The basic diff is ER model is a normalized model becoz in oltp we don't have the concept of dim model

       where as dim model is a denormalized model where we can use multi dim analysis

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In the E-R modeling the data is represented in entities and attributes and it's in the denormalized form.. In the dimensional modeling the data is represented in form of facts and dimension's the fact's contain only neumaricals and foreign key's and the dimension's are used to refer's the data from fact table's using these fact and dimensions we can form OLAP cubes for analysis ..which are useful for decision support for management

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  • Nov 6th, 2006

ER modeling: a view of data from data processing.

MD modeling: a view of data from business porcessing.

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E-R Modeling is a model for OLTP, optimized for Operational database, namely insert, update, delete data and stressing on data relational integrity.Dimensional Modeling is a model for OLAP, optimized for retrieving data because it's uncommon to update or delete the data.

E-R model views the real world as entities and attributes.

entities are related to each other and attributes are the properties of the entity.
eliminates data redundancy
high transactional performance

dimension modelling
comprises of fact and dimension tables.
the dimension tables cannot be further normalised

ER Model

Process : Normalization
Join : More ( n-1)
Detail Data
Size: MB to GB
Data : Current Data
user's : More than 1000
Data: Volatile.

Dimensional Modeling

Process: Denormalization
Join: Less
Data: Summarized at lower level
Size: GB to Tb
Data: Historical Data ( 10-15 yrs)
Using only top management
Non Volatile

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Sreedhar Lokaray

  • Nov 3rd, 2011

I think the answer the best suits this question is as below:

Entity - Relationship Modelling:-

Removes data redundancy.
Ensures data consistency.
Expresses relationship between the entities.

Dimension Modelling:-

Captures critical measures.
Views along dimensions.
Useful to business users.

Read difference between OLTP & OLAP to understand the above.

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  • Jan 30th, 2018

ER represent the logical design technique that seeks to eliminated the data redundancy It shows the relationship between the data.
DM is a logical technique that seek to present the data in standard intuitive to allow high performance access.

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