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Purdue MGMT 38200 - Data SDLC

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MGMT 382 1st Edition Lecture 7Last Lecture Current Lecture Outline I. Why Systems Fail II. DataIII. File Processing Current LectureI. Why Systems Fail i. 33% cancelled before they get to customer ii. 50% cost almost double the original estimate iii. only 20% are successful; 80% fail! b. Unclear or missing requirements i. Missing or incorrectly gathered during anaylsis phase ii. Can come form misdiagnosing the problem in the identification and selection phase (address symptom, not problem) c. Skipping SDLC Phases i. To cut time and/or cost phases are cut short or eliminated ii. Testing is one of the first things to be cut (along with systems documentation) iii. Analysis and design phases are also victims 1. Cuts inadequate analysis lead to missing or unclear requirements 2. Cuts in design lead to less than optimal solution options or problems in development and implementation iv. Failure to manage project scope 1. Scope creep: project expands beyond initial stated requirements (usually from the user) 2. Feature creep: developers add features that were not part of the initial requirement 3. Also can come form failure to define the scope of the project (back in initiation and planning or identification and selection)v. Changing Technology1. Have to be forward thinking 2. Can not stand still for too long 3. Must really understand your industry/field very well These notes represent a detailed interpretation of the professor’s lecture. GradeBuddy is best used as a supplement to your own notes, not as a substitute.vi. Failure to manage the project plan 1. Plan is living, breathing (things change) 2. Best, worst, average, probably 3. Constant monitoring 4. Do not panic II. Data: meaningful facts, text, graphics, images, sound, video segments a. Information: data processed to be useful in decision making b. Database: an organized collection of logically related data c. Metadata: data that describes data III. Disadvantages with file processing i. Program-data dependence- all programs maintain metadata for each file they use ii. Data redundancy (duplication of data)- different systems/programs have separate copies of the same data iii. Limited data sharing- no centralized control of the data iv. Lengthy development times – programmers must design their own file formatsv. Excessive program maintenance- 80% of information systems


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