Marathon class psbd

1. MARATHON CLASS Edi Purnomo Putra Lecture Code : D5386

2. Normalisasi • Tujuan Normalisasi • Update anomalisinsert, update, delete • Functional dependency • Full functional dependency nilainim, KdMtk • Partial dependency namabarangidbarang

3. Normalisasi normalisasi adalah suatu teknik Formal Dalam Menentukan atribut dan menghasilkan kumpulan relasi yang bertujuan untuk menyediakan kebutuhan data yang diperlukan oleh perusahaan • A technique for producting a set of relation with desirable properties, given data reqruirements of an enterprise

4. Tujuan Normalisasi 1) Menjamin struktur data yang konsisten. 2) Kerangkapan data yang minimal. 3) Stabilitas struktur data yang maksimal 1) Meminimalkan Jumlah Kapasitas Penyimpanan Yang Diperlukan Untuk menyimpan data. 2) Meminimalkan resiko data yang tidak konsisten dalam suatu basis data. 3) Meminimalkan kemungkinan update dan delete anomaly. 4) Memaksimalkan stabilitas dari struktur data Manfaat Normalisasi

7. Datawarehouse • Karakteristik DWH • ETL(Extract, transform, loading) • Datamart vs DWH

8. Karakteristik • Subject oriented Customer, product, sales • Integrated Data konsisten Male, M, Ma  Male • Nonvolatile Tidak bisa diubah  refresh  scd(Slow Changing Dimension) • Time variant Mingguna, bulanan, tahunandimensi waktu

9. ETL • Extract Ekstract data dari ODS /OLTP(OPERASIONAL DATA SOURCE) • Transform Penyamaan data JL, jalan, JLN JL Melakukan kalkulasi aggregate • Load Masukan data ke DWH/Data Mart

10. Datamart VS DWH • Data mart • 1 subject • Bagian dari data warehouse • Relative Sebentar • DWH • Beberapa subject • Implementasi waktu lama

11. ER • Fan trap • Chasm trap • Participant disjoint • Strong entity • Weak entity • Degree relation • Recursive • Single value atribute • Multivalue attribute

12. Prticiapant Disjoint • Participant And / or • Join disjoin Optional and mandatory

13. Participant Disjoint

14. Participant Disjoint

15. Optional OR

16. Mandatory Or

17. Degree Degree of a Relationship Number of participating entities in relationship. Relationship of degree : two is binary three is ternary four is quaternary.

18. Binary relationship called POwns

19. Ternary relationship called Registers

20. Quaternary relationship called Arranges

21. Recursive relationship called Supervises with role names

22. Attributes • Attribute – Property of an entity or a relationship type. • Attribute Domain – Set of allowable values for one or more attributes.

23. Attributes • Simple Attribute – Attribute composed of a single component with an independent existence. • Composite Attribute – Attribute composed of multiple components, each with an independent existence.

24. Attributes • Single-valued Attribute – Attribute that holds a single value for each occurrence of an entity type. • Multi-valued Attribute – Attribute that holds multiple values for each occurrence of an entity type.

25. Attributes • Derived Attribute – Attribute that represents a value that is derivable from value of a related attribute, or set of attributes, not necessarily in the same entity type.

26. Entity Type • Strong Entity Type – Entity type that is not existence-dependent on some other entity type. • Weak Entity Type – Entity type that is existence-dependent on some other entity type.

27. • Fan Trap – Where a model represents a relationship between entity types, but pathway between certain entity occurrences is ambiguous. • Chasm Trap – Where a model suggests the existence of a relationship between entity types, but pathway does not exist between certain entity occurrences. Trap

28. An Example of a Fan Trap

29. Semantic Net of ER Model with Fan Trap • At which branch office does staff number SG37 work?

30. Restructuring ER model to remove Fan Trap

31. Semantic Net of Restructured ER Model with Fan Trap Removed • SG37 works at branch B003.

32. An Example of a Chasm Trap

33. Semantic Net of ER Model with Chasm Trap • At which branch office is property PA14 available? Mengawasi, mengatur

34. ER Model restructured to remove Chasm Trap

35. Semantic Net of Restructured ER Model with Chasm Trap Removed

36. Key Type • Primary key NIM, KDMataKuliah • Composite key KdMatakuliah+NIM • Foreign key • Candidate key • Alternate key

37. Aggregate • Sum • Avg • Min • Max • Count

38. Intersect, except,union

Marathon class psbd

Marathon class psbd

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