1. Chapter 4 Operations and Transactions The Strategic Management of Information Systems

2. Transaction Processing System Input Output Process

3. Two Levels of Planning l Systems Planning –Gives Managers, Users, and Information Systems Personnel Projects –Establishes what should be done –Sets a budget for the total cost of these projects l Systems Project Planning –Setting a plan for the development of each specific systems project

4. Systems Professional Skills l Systems Planning –Form project team after proposed systems project is cleared for development l Systems Analysis –Business Systems Analysts knowledgeable in business l General Systems Design –Business Systems Analysts l Systems Evaluation and Selection –Business Systems Analysts l Detailed Systems Design –Wide Range of Systems and Technical Designers l Systems Implementation –Systems analysts, programmers, and special technicians

5. Effective Leadership Style l Autocratic Style –Crisis-Style Management –Used to Correct Major Problem, such as Schedule Slippage l Democratic Style –Team-oriented Leadership –Gives each team member the freedom to achieve goals which he/she helped set l Laissez-Faire Style –Highly-motivated, Highly-Skilled Team Members –People who work best alone

6. Project Management Skills l Planning –States what should be done –Estimates how long it will take –Estimates what it will cost l Leading –Adapts to dynamics of enterprise and deals with setbacks –Guides and induces people to perform at maximum abilities l Controlling –Monitors Progress Reports and Documented Deliverables –Compares Plans with Actuals l Organizing –Staffs a Systems Project Team –Brings together users, managers, and team members

7. Project Management l Gantt Chart l Pert Chart

8. Gantt Chart l Compares Planned Performance against actual performance to determine whether the project is ahead of, behind, or on schedule l Schedule a complete systems project by phases

9. PERT Chart l Four Steps –Identify Tasks –Determine Proper Sequence of Tasks –Estimate the Time Required to Perform each Task –Prepare Time-Scaled Chart of Tasks and Events to Determine the Critical Path

10. PERT Chart l Estimate, Schedule, and Control a network of interdependent tasks l Shown by arrows, nodes, or circles l Determine minimum time needed to complete a project, phase, or task l Critical Path –Minimum time needed to complete a project or phase l Program, Evaluation and Renew Technique –Total of the most time-consuming chain of events

11. CASE l Computer-Aided Systems and Software Engineering l Increase Productivity of Systems Professionals l Improve the Quality of Systems Produced l Improve Software Maintenance Issue

12. CASE l Includes: –workstations –central repository –numerous modeling tools –project management –Systems Development Life Cycle Support –Prototyping Applications –Software Design Features

13. Central Repository l Models Derived from Modeling Tools l Project Management Elements l Documented Deliverables l Screen Prototypes and Report Designs l Software Code from Automatic Code Generator l Module and Object Libraries of Reusable Code l Reverse Engineering, Reengineering, and Restructuring Features

14. Software Maintenance l Reverse Engineering –Extract original design from spaghetti-like, undocumented code to make maintenance change request –Abstract meaningful design specifications that can be used by maintenance programmers to perform maintenance tasks l Reengineering –Examination and changing of a system to reconstitute it in form and functionality –Reimplementation l Restructuring –Restructures code into standard control constructs l sequence, selection, repetition

15. Business Rules For Data l Basic selection of what data elements are of interest, what are their characteristics (data type and acceptable range - also called syntactic structure) l How they are related to, or dependent on, each other in a business sense (key, foreign key and referential constraint rule - also called the semantic structure) l Data Integrity Rules

16. Data Rationalization l Identification of data synonyms and homonyms across multiple and disparate data sources and the creation of a map that points back to their original sources.

17. Data Access Gateway l A system that sits between end users (usually in PC networks) and a legacy database, that accepts data read requests (expressed as SQL statements), converts the requests to legacy access method instructions, and then provides the resulting data to the users. The data flow is one-way read-only.

18. Structured Analysis Identifies l the functions or activities which are to be handled by the system l the external entities which interact with the system l the logical data stores, and l the data flows among all the the above l Data flow diagrams (DFD) are used to diagrammatically describe the elements.

19. Conversion into Normalized Record Types l For every data flow which either enters or emanates from a data store (in the leaf level DFDs), the integral data elements are identified l For every data store, a list of the data elements which are entering and emanating are drawn up l The dependencies among all the data elements are analyzed, and the normalization rules are applied in steps so that at every step a given relation is split into more simple relations –Every relation has a key which consists of one or more data elements –Every non-key data element functionally depends on that entire key and not on part of it –No non-key data element depends on any other non-key data element in the relation (there are no transitive dependencies)

20. Enter exams dates & rooms D1Exams File List of Exams details Details of Exams Notify Lectures Details of Exams Notify Students for lecturer for students Conversion into Normalized Record Types

21. Part Description for Model for General Motors Part #123 that is supplied by GM was assembled on bus 456 on May 28, 1996 is decomposed into the following elementary sentences: a). A part... is supplied by a manufacturer... b). A part... was assembled on a bus... c). The assembly [part*bus] was performed on a date...

22. Manufacturer (name) Supplier of Supplied of Part (p#) Part Distribution Model for General Motors

23. Relationship Types a). One-to-one (1:1): means that an occurrence if one OT uniquely determines an occurrence of other OT - and vice-versa b). One-to-many (1:n): means that an occurrence of one OT determines an occurrence of the other OT - but not vice- versa c). Many-to-many (n:m):means that an occurrence of one OT can be related to many occurrences of other OT - and vice-versa

24. Bus (License #) Part (p#) Supplier Manu- facturer (name) Date of Assembly Date (Calc. date) Assembly Distribution Model

25. Normalization Model l The SA/Normalization method is based on the use of decomposition rules, which enable one to decompose tables/relations. –Database design starts with flat tables/relations, each of which is created out of a data stores in the DFDs and then decomposed into the normal form relations. No conceptual schema of the enterprise is created to express the semantics of its information structure. l The SA/IA method is based on the use of grouping rules which map simple relationships in the binary-relationship data model onto normal form relationships. –The relational model and the normalization method have been criticized for being too detailed to use at the initial design stage, and for lacking a semantic structure for making unambiguous choices in modeling the enterprise. –The IA method incorporates a semantic model of the enterprise which captures its essential semantic features from which the normal form relations are derived.

26. l Basic selection of what data elements are of interest, what are their characteristics (data type and acceptable range - also called syntactic structure) l How they are related to, or dependent on, each other in a business sense (key, foreign key and referential constraint rule - also called the semantic structure) l Data Integrity Rules Business Rules For Data

27. Data Rationalization l Identification of data synonyms and homonyms across multiple and disparate data sources and the creation of a map that points back to their original sources.

28. Data Access Gateway l sits between end users (usually in PC networks) and a legacy database l accepts data read requests (expressed as SQL statements) l converts the requests to legacy access method instructions l provides the resulting data to the users l data flow is one-way read-only.

29. Data Design l Define all the entities to be dealt with and the relationships between them l Transform the conceptual design into logical design wherein all the views are combined and all the resulting data elements are defined and the data structure is syntactically and semantically determined l Normalize this logical design for mathematically minimized redundancy and maximized integrity l Transform this logical design to a physical design where the underlying RDBMS, hardware, and use patterns are taken into account l Develop the SQL DDL code specific to each RDBMS vendors product is generated

30. Data Warehouse l An intermediate, read-only store (usually based in a purchased RDBMS product) and the programs that manage it. l Contains recent and summarized data extracted from across some or all of the legacy data systems l Presents a subject-based view

31. De-Normalization l The process of selectively –combining two or more normalized tables into one, or –decomposing one normalized table into two or more

32. Entity Relationship Diagrams (ERDs) l A method of documenting and visualizing a conceptual data model.

33. Functional Dependency l Mathematical term for the key relationship (using rational terminology) between data elements. A data element (attribute) that is functionally dependent on another data element (the key) will always exist in a relation (table) such that a unique value for the key will always determine or locate or define a unique value of the dependent.

34. Metadata l Data about data that is generally extracted from an existing system or created for a new system and stored in a design repository for developers to use in maintaining or extending the system during its lifecycle l Metadata refers to the table, attribute, and key definitions contained in the catalog of a relational database. It can also mean the business rules for data designed for a new design, or the business rules for data thought to be enforced in a legacy system (semantic data structure, sometimes called meta-data, or meta2 data). l The actual syntactic and semantic data structure (not just what the documentation might say), including a complete synonym and homonym map, plus the business rules for data that are actually being enforced in the legacy system.

35. Normalization l The process based on the business rules for data –a set of data elements (attributes) are arranged in a mathematically minimum set of tables (relations), within which all the attributes are dependent on a primary key attribute (the key).

36. Relational Model l The Relational Model for data design is the foundation of the relational database and the industry that produces the engines that run them. l It puts data design (and data modeling) on a formal, mathematical footing.

37. Advantages of Data Query l slice and dice dynamic query support l standard high-level access language (SQL) l minimum data redundancy l self-protecting data integrity –no insert, delete and update anomalies

38. GM Parts Example Part #123 that is supplied by GM was assembled on bus 456 on May 28, 1996 is decomposed into the following elementary sentences: a). A part... is supplied by a manufacturer... b). A part... was assembled on a bus... c). The assembly [part*bus] was performed on a date...

39. Manufacturer (name) Supplier of Supplied of Part (p#) GM Parts Example

40. Relationship Types a). One-to-one (1:1): means that an occurrence if one OT uniquely determines an occurrence of other OT - and vice-versa b). One-to-many (1:n): means that an occurrence of one OT determines an occurrence of the other OT - but not vice- versa c). Many-to-many (n:m):means that an occurrence of one OT can be related to many occurrences of other OT - and vice-versa

41. Bus (License #) Part (p#) Supplier Manu- facturer (name) Date of Assembly Date (Calc. date) GM Parts Assembly Example