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Data Modeling [Comparison of data modeling techniques ] PowerPoint Presentation
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Data Modeling [Comparison of data modeling techniques ]

Data Modeling [Comparison of data modeling techniques ]

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Data Modeling [Comparison of data modeling techniques ]

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  1. Data Modeling[Comparison of data modeling techniques ] By Renjini Sindhuri

  2. Contents • Introduction • E-R modeling • Peter Chen • Information Engineering • Barkers Notation • IDEFIX • UML modeling • XML modeling • X- Entity modeling • XUML • Conclusion

  3. Introduction • Data modeling is the act of exploring data oriented structures. • Examines and compares different data modeling techniques • In the data modeling techniques we have traditional modeling and object oriented modeling of data

  4. E-R modeling • It is a conceptual data model that views the real world as consisting of entities and relationships • It is used to transform relational tables that are easy to understand that enables easy communication with the end user • Peter –Chen developed E-R model

  5. Peter –Chen notation • Entities are represented in the squared cornered and circles as attributes • Many –Many relationships can be represented without associative entity • Relationship itself has attributes and are considered as objects • It failed to represent unique identifier

  6. Peter Chen’s Model

  7. Information Engineering model • Developed by Clive Finkelstein • Entities are represented in the squared cornered and attributes are not shown at all they are shown in a separate list called entity list • Relationships like mandatory 1 and many can be represented • Unique identifiers are not represented

  8. Information Engineering modeldiagram

  9. Barkers Notation • Adopted by Oracle corporation for its CASE method • Entities can be represented by round cornered rectangle • Same entity can be represented for role an interaction or another kind of association • Relationship names are prepositions and not verbs • Unique identifiers can be represented by hash marks next to the attribute

  10. Barkers Notation diagram

  11. IDEFIX Notation • It is a modeling technique that is used by many branches of the United States Federal government • A relationship name is a verb • IDEFIX shows subtypes as separate entity boxes • IDEFIX permits multiple inheritance and multiple type hierarchies

  12. IDEFIX diagram

  13. UML • UML is an object modeling technique • It models object classes instead of entities • In the object oriented world the relationships are called as associations • Cardinality and optionality in UML is conveyed by characters or numbers • Express in the form of more complex upper and lower limits • UML introduces a small flag that includes text describing any business rules

  14. UML diagram

  15. XML Notation • Describing data and interchanging structured and unstructured data on the Internet • It is a universal language of data on web • XML tags are used to create data structures • XML documents have been widely used for interchanging data between heterogeneous systems.

  16. XML notation • An example of XML notation

  17. X-Entity model • Conceptual model of XML uses X entity model in order to represent additional features • The entity can be denoted by ‘E’ • ({A1,….An},{R1,…Rm},{D1,….Dk}) • Each attribute A is associated with a domain Dom(Ai) Which specifies its value set Cardinality is denoted by Card(Ai)=(min,max)

  18. X entity model diagram

  19. XUML • XUML comprises the characteristics of XML and UML2. • It is used to express the containment semantics more explicitly • Supporting the concept of Business Components • Specifying the data dependencies in multiple context

  20. XUML diagram UML and XUML model of a book store

  21. Comparison of data modeling techniques

  22. Comparison of Data modeling techniques

  23. Comparison of Data Modeling techniques

  24. Comparison of Data Modeling techniques

  25. Advantages of XUML • XUML can express the containment semantics more accurately. • Support the concept of Business Component. • Can specify the data dependencies in multiple context.

  26. Contd.. • XUML is more expressive, precise and understandable. • More rigorous and accurate.

  27. Conclusion • By comparing the aesthetic simplicity, completeness, language notation (relationship) Mr. Barker's notation is favorable for requirement analysis model • XML is used in recent trends it follows a standard format for representing structured and semi structured data on web • X-Entity model has the advantages of both XML schemas and extends the ER model so that it can explicitly represent important features of XML schemas • The distinctive features of XUML made this technique of data modeling the latest trend for conceptual modeling of data.

  28. References • 1. Conceptual Modeling of XML schemas, Bernadette Farias Losio,Ana Carolina Salgado , Year: 2003,Publisher: ACM • 2. XML conceptual modeling with XUML, HongXing Liu HuaZhong University of Science and Technology, P. R. China, YanSheng Lu HuaZhong University of Science and Technology, P. R. China,Qing Yang Wuhan Uni Pages: 973 – 976, Year of Publication: 2006, Publisher: ACM Press • 3. PETER PIN-SHAN CHEN, “The Entity Relationship Model-Toward a Unified View of Data” , Massachusetts Institute of Technology, ACM Transactions on Data base System Volume1, Issue 1,Publisher-ACM • 4. Data modeling in the understanding database course: adding UML and XML modeling to the traditional content. Journal of Computing Sciences in Colleges, Volume 17, Issue 5 (April 2002)

  29. References • 5.Data Modeling101. 6.A comparison of Data Modeling ,David C Hay,Essential Strategies Inc,October 1999.