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Comparative Study of E-R Modeling and Dimensional Modeling 
PRN 
NAME 
12030121020 
Shivam Tyagi 
12030121026 
Aniket Srivastava 
12030121028 
Amit Shivsharan 
12030121030 
Karuna Kak 
BCA (2012-15) 
Division A
Entity Relationship Modeling 
•Theentity-relationship(E-R)datamodelisbasedonaperceptionofarealworldthatconsistsofasetofbasicobjectscalledentities,andofrelationshipsamongtheseobjects. 
•StepsinE-RModeling: 
Identify the entitiesLook for general Nouns in requirement specification document, which are of business interest to users. 
IdentifythekeyattributesforeveryentityIdentifytheattributeorsetofattributeswhichcanidentifyinstanceofentityuniquely 
Find the associations between entitiesIdentify the natural relationship and their cardinalities between the entities. 
Complete E-R Diagram Draw complete ER diagram with all attributes including primary key . 
2
3 
Symbol 
Description
E-R Modeling Example 
4
Star schema 
•Starschemaisadimensionmodelingtechnique. 
•ThedimensiontablearerelatedtoeachotherwithM:Mrelationshipandaredenormalized. 
•ThefacttableisnormalisedbecauseithasI:Mrelationshipwithotherdimensions. 
•Example:Items,Branch,Location,andTimeareDimensionTableswhicharedenormalized.Totalsaleswithtime_key,item_key, branch_keyandlocation_key(primarykeysofalldimensiontables)istheFactTablewhichisnormalized. 
5
6 
Star Schema Example
Snowflake schema 
•Thesnowflakeschemaisadimensionmodelingtechnique. 
•"Snowflaking"isamethodofnormalisingthedimensiontablesinastarschema.Dimensiontablesgetpartiallynormalised. 
•Theprinciplebehindsnowflakingisnormalisationofthedimensiontablesbyremovinglowcardinalityattributesandformingseparatetables. 
•Whenwedonotaccessaparticulartableorwedon’tretrieveanythingfromthetablefrequently,webreakthetablewith1:Mrelationship. 
•Example:Items,Branch,Location,andTimeareDimensionTableswhicharedenormalized.Totalsaleswithtime_key,item_key,branch_keyandlocation_key(primarykeysofalldimensiontables)istheFactTablewhichisnormalized.Alsoitemsdimensionhadcityfieldsandlocationdimensionhadacityfieldswhichwereretrievedveryinfrequentlythereforetheyarebreakdownintoseparatedimensiontables. 
7
8 
Snowflake Schema Example
Comparative Study of ER Modeling and Dimensional Modeling 
E-R Modeling 
Dimensional Modeling 
SupportsOLTP(OnlineTransactionProcessing) 
SupportsOLAP(OnlineAnalyticalProcessing) 
Entitiesarelinkedwithaseriesofjoins. 
Entitiesarelinkedwithaseriesofjoins. 
Normalized 
Denormalized 
Removesredundancy. 
Permitsredundancy. 
Ifmodelismodified,theapplicationaremodified. 
Itisextensibletoaccommodateunexpectednewdataelementsandnewdesigndecision. 
Itisvariableinstructureandveryvulnerabletochangesintheuser’squeryinghabits. 
Itisrobust.Thedimensionalmodeldesigncanbedoneindependentofexpectedquerypattern. 
Themodelforenterpriseisveryhardforpeopletovisualizeandkeepintheirheads. 
Thismodeliseasyandunderstandable.
Comparison between ER Modeling and Dimension Modeling

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Comparison between ER Modeling and Dimension Modeling

  • 1. Comparative Study of E-R Modeling and Dimensional Modeling PRN NAME 12030121020 Shivam Tyagi 12030121026 Aniket Srivastava 12030121028 Amit Shivsharan 12030121030 Karuna Kak BCA (2012-15) Division A
  • 2. Entity Relationship Modeling •Theentity-relationship(E-R)datamodelisbasedonaperceptionofarealworldthatconsistsofasetofbasicobjectscalledentities,andofrelationshipsamongtheseobjects. •StepsinE-RModeling: Identify the entitiesLook for general Nouns in requirement specification document, which are of business interest to users. IdentifythekeyattributesforeveryentityIdentifytheattributeorsetofattributeswhichcanidentifyinstanceofentityuniquely Find the associations between entitiesIdentify the natural relationship and their cardinalities between the entities. Complete E-R Diagram Draw complete ER diagram with all attributes including primary key . 2
  • 5. Star schema •Starschemaisadimensionmodelingtechnique. •ThedimensiontablearerelatedtoeachotherwithM:Mrelationshipandaredenormalized. •ThefacttableisnormalisedbecauseithasI:Mrelationshipwithotherdimensions. •Example:Items,Branch,Location,andTimeareDimensionTableswhicharedenormalized.Totalsaleswithtime_key,item_key, branch_keyandlocation_key(primarykeysofalldimensiontables)istheFactTablewhichisnormalized. 5
  • 6. 6 Star Schema Example
  • 7. Snowflake schema •Thesnowflakeschemaisadimensionmodelingtechnique. •"Snowflaking"isamethodofnormalisingthedimensiontablesinastarschema.Dimensiontablesgetpartiallynormalised. •Theprinciplebehindsnowflakingisnormalisationofthedimensiontablesbyremovinglowcardinalityattributesandformingseparatetables. •Whenwedonotaccessaparticulartableorwedon’tretrieveanythingfromthetablefrequently,webreakthetablewith1:Mrelationship. •Example:Items,Branch,Location,andTimeareDimensionTableswhicharedenormalized.Totalsaleswithtime_key,item_key,branch_keyandlocation_key(primarykeysofalldimensiontables)istheFactTablewhichisnormalized.Alsoitemsdimensionhadcityfieldsandlocationdimensionhadacityfieldswhichwereretrievedveryinfrequentlythereforetheyarebreakdownintoseparatedimensiontables. 7
  • 9. Comparative Study of ER Modeling and Dimensional Modeling E-R Modeling Dimensional Modeling SupportsOLTP(OnlineTransactionProcessing) SupportsOLAP(OnlineAnalyticalProcessing) Entitiesarelinkedwithaseriesofjoins. Entitiesarelinkedwithaseriesofjoins. Normalized Denormalized Removesredundancy. Permitsredundancy. Ifmodelismodified,theapplicationaremodified. Itisextensibletoaccommodateunexpectednewdataelementsandnewdesigndecision. Itisvariableinstructureandveryvulnerabletochangesintheuser’squeryinghabits. Itisrobust.Thedimensionalmodeldesigncanbedoneindependentofexpectedquerypattern. Themodelforenterpriseisveryhardforpeopletovisualizeandkeepintheirheads. Thismodeliseasyandunderstandable.