MANAGING INFORMATION RESOURCES

1. MANAGING INFORMATION RESOURCES Andreas Rio, M.Eng. contact@andreasrio.com

2. Managing Information Resources It explores the management of: • Data • Information • Knowledge

3. DATA

4. Managing Data • Data is primarily facts about entities, such as individual employees, customers, parts, or transactions. • Well-structured data records hold a set of attributes that describe each entity. • Database management systems (DBMSs) are the main tools for managing these entities.

5. Managing Data The Three Level Database Model

6. The Three Level Database Model • Level 1 contains the various “user views" of the corporate data. • Level 2 encompasses all an organization’s relevant data under the control of the data administrators. • Level 3 specifies the way the data is physically stored. The advantage of the model: • Individual application programs in Level 1 do not need to be changed when the physical layer (Level 3) changes.

7. Database Environment Application Programs User Interface CASE Tools Repository Database DBMS

8. Database Environment • Computer-aided software engineering (CASE) Tools • Peranti otomasi untuk perancangan database dan program aplikasi • Repository • Tempat penyimpanan terpusat yang berisi definisi data, hubungan data, format layar dan laporan, serta komponen-komponen sistem lain • Berisi metadata yang diperlukan untuk pengelolaan database dan komponen-komponen lain sistem informasi

9. Contoh Metadata

10. Database Environment • Database Management System (DBMS) • Software yang ditujukan untuk mendefinisikan, menciptakan, memelihara, dan menyediakan akses terkontrol terhadap database dan repository • Contoh DBMS: Microsoft Access, Visual FoxPro, Informix, Oracle, dll

11. Contoh DBMS Access

12. Database Environment • Database • Kumpulan data yang saling terkait • Perbedaan dengan repository: • Repository berisi definisi data • Database berisi data • Sebuah database berisi kumpulan dari tabel

13. Contoh Database

14. Four Data Model 1. Hierarchical Model 2. Network Model 3. Relational Model 4. Object Model

15. Hierarchical Model • Each data element is subordinate to another in a strict hierarchical manner. • It is like the boxes on an organization chart.

16. Hierarchical Model Dosen Siti Nurbaya Dosen Ashadi Pengantar Basis Data Pemrograman C Matematika I Rudi Asti Dina Dina Edi Ita Edi

17. Network Model • In the network model, each data item can have more than one parent; assembly parts lists illustrate this structure.

18. Network Model Dosen Siti Nurbaya Dosen Ashadi Pengantar Basis Data Pemrograman C Matematika I Rudi Asti Dina Edi Ita

19. Relational Model • In the relational model, it is up to the DBMS to find the related items, based on the values of specified data fields. • All employees of a certain department are found by searching for the department number in each employee record. • Relational systems allow people to create relationships among data on the fly.

20. Relational Model • Merupakan model data yang paling populer saat ini • Menggunakan model berupa tabel berdimensi dua (yang disebut relasi atau tabel) • Memakai kunci tamu (foreign key) sebagai penghubung dengan tabel lain

21. Relational Model

22. Relational Model Relasi atau tabel Sebuah baris atau tuple Kardinalitas Domain NILAI (A, B, C, D, E) Atribut atau kolom

23. Relational Model • Beberapa sifat yang melekat dalam relasi: • Tidak ada baris yang kembar • Urutan tupel tidak penting • Setiap atribut memiliki nama yang unik • Letak atribut bebas • Setiap atribut memiliki nilai tunggal dan jenisnya sama untuk semua baris

24. Object Model • The object model can be used to store any type of data, whether a traditional name or address, an entire spreadsheet, a video clip, a voice annotation, a photograph, or a segment of music. • The tenets of objects have become increasingly important in the world of computing. • They become even more important in the world of Web Services because the XML modules utilize object principles.

25. Object Model • Centers around objects and classes • Involves inheritance • Encapsulates both data and behavior

26. Object Model Object Oriented EER Entity type Class Entity instance Object Relationship Association Inheritance of attributes Inheritance of attributes No representation of behavior Inheritance of behavior Object-oriented modeling is frequently accomplished using the Unified Modeling Language (UML)

27. Object Model UML class and object diagrams Class diagram showing two classes Class diagram shows the static structure of an object-oriented model: object classes, internal structure, relationships.

28. CASE STUDY Enterprise Resource Planning (ERP) Mosanto Company

29. Enterprise Resource Planning 1. Clean up Data Definitions 2. Control Shared Data 3. Manage Data Distribution 4. Maintain Data Quality

30. Enterprise Resource Planning Case Study: Monsanto Company

31. Enterprise Resource Planning Monsanto established 3 large enterprise wide IT projects: • To redevelop operational and financial transaction systems using SAP • To develop a knowledge-management architecture, including data warehousing • To link transaction and decision support systems via common master data, known as enterprise reference data (ERD)

32. Enterprise Resource Planning • They created a distributed SAP architecture, with separate instances of SAP for reference data, finance, and operations in each business unit. • The master reference data integrates these distributed components. • To convert SAP data to knowledge, Monsanto used data warehouses. The sole source of master data is the ERD, but the data can be distributed wherever it is needed. • To get corporate data in shape, Monsanto created a department called ERD Stewardship to set data standards and enforce quality.

33. INFORMATION

34. Four Types of Information • Data warehouses address internal and external record-based data. • Document management and content management address internal and external document-based data.

35. Data Warehouse • Data warehouses house data used to make decisions. • The data is generally obtained periodically from transaction databases, thus presenting a snapshot at a point in time. • The most common data warehoused is customer data, used to discover how to more effectively market to current customers as well as non-customers with the same characteristics.

36. Document Management • To improve the publishing process • To support communications among people and groups • To support organizational processes

37. Document Management • Even in today’s Internet-rich world, paper still plays a major role in most enterprises. • There is also a need to move seamlessly between digital and printed versions of documents; hence, the importance of document management. • The field of electronic document management (EDM) uses new technologies to manage information resources that do not fit easily into traditional databases.

38. Document Management 1. To improve the publishing process

39. Case Study: HICSS Personal Proceeding • A month before the conference, participants can use a Web site to choose 20 papers they would like to have in their personal paper proceedings. • The papers are printed on a Xerox Docutech machine with their name on the cover, and delivered to them at the conference. • Additional papers can be printed individually at the conference, on demand.

40. Document Management 2. To support communications among people and groups

41. Case Study: Tapiola Insurance Group • This Finnish insurance group formerly offered 150 kinds of insurance policies and had 300 different insurance policy forms—half in Swedish and half in Finnish—because both are official languages in Finland. • The policy forms were preprinted by an outside print shop. To personalize the forms and cut costs, Tapiola brought the process in-house and defined just four forms, which are printed on demand.

42. Document Management 3. To support organizational process

43. Case Study: Tennessee Valley Authority • The nuclear division of this large U.S. power supplier revamped its maintenance management system. • TVA spends more than $48 million a year creating maintenance work orders and then planning and performing the work. • One plant alone processes 14,000 work orders a year. • The new process electronically combined maintenance orders in one system with procedural document management in another system

44. Case Study: Tennessee Valley Authority • Work orders are generated electronically and then routed for approval, with the most current drawings and procedures electronically attached. • The documents are indexed by, so maintenance people can review past activity and better plan for the future.

45. KNOWLEDGE

46. Content Management

47. 3 Phases Content Management 1. Content Creation and Acquisition 2. Content Administration and Safeguarding 3. Content Deployment and Presentation

48. Content Creation and Acquisition • Content creation and acquisition need to focus on creating content quality. • The best organizational structure is to distribute content creation and maintenance to content-expert employees. • But to avoid anarchy, these dispersed experts should be directed centrally, and use centrally-created formats and an automated workflow system that moves their work along.

49. Content Administration & Safeguarding • The emphasis in this phase, like any operational phase, is efficiency. • Content management tools can be used to identify types of content and the business rules that apply to each type. • While content creation should be distributed, content administration should be centralized.

50. Content Deployment & Presentation • The emphasis in this phase should be effectiveness: presenting the content so that it attracts visitors, allows them to navigate the site easily, and leads them to the desired actions. • Because this phase can determine the success of a firm’s e-commerce efforts, it’s best to design a Web site beginning with this phase, then move on to ensuring content quality and processing efficiency.