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Transforming Data by Calculation

Transforming Data by Calculation. Author: Professor J.N. Oliveira Presentation by: Mohammadreza Vali zadeh. outline. Why data transformation? Introducing the Point-free Transform Data Structures transformation Data Impedance Mismatch conclusion. Why data transformation?.

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Transforming Data by Calculation

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  1. Transforming Data by Calculation Author: Professor J.N. Oliveira Presentation by: MohammadrezaValizadeh

  2. outline • Why data transformation? • Introducing the Point-free Transform • Data Structures transformation • Data Impedance Mismatch • conclusion

  3. Why data transformation? • Watch a calculator

  4. … • square root Inside a machine these processes happen very much

  5. … • Such processes happen very much in software systems too. • Each layers stay in different programming paradigms (object-oriented database, relational database)

  6. … • Data transformation: Middle-ware code to bridge the gap between two different technology layers • Main motivation for data calculation is the need for data mapping

  7. … • Different data models can be compared via abstraction and representation • Three kinds of fault solution • Loss of data • Confusion among data Data representation • Wrong computation Data processing Helping in preventing any of these from happening in software designs is the main aim of this paper

  8. Introducing the Point-free Transform • Converting predicate logic formula into binary relations by removing variables and quantifier(Algebra of programming) • The main principle of the PF-transform: “everything is a binary relation” A R B

  9. Data Structures transformation • Data structure: Varity notation , programming language and paradigm

  10. … • Mapping scenario (transformation) • Type-level mapping of a source data model to a target data model • Two maps (map forward & map backward) between source & target data

  11. … • The transcription level mapping of source operation to target operation

  12. … • Sample: Datatype In haskell: In c:

  13. … • In haskell:

  14. Data Impedance Mismatch • Different data models can be compared via abstraction or representation (in transformation) • It has complexity The least impedance mismatch is between a data type and itself

  15. conclusion • Mathematical approach to data transformation is presented • Converting data models to each other • Try to solve the impedance problem Consequence: finding problems in system • Future: Apply transform in practice and Laplace

  16. Thank you for your attention

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