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MGMT 382: Vasa Case and Databases

by: Emily McIlhattan

MGMT 382: Vasa Case and Databases MGMT 382

Marketplace > Purdue University > Business, management > MGMT 382 > MGMT 382 Vasa Case and Databases
Emily McIlhattan
GPA 3.72
Management Information Systems
Dr. Dejoie

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About this Document

This document includes the lecture over the Vasa Case, and the lecture over Databases!
Management Information Systems
Dr. Dejoie
Class Notes
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This 5 page Class Notes was uploaded by Emily McIlhattan on Thursday February 12, 2015. The Class Notes belongs to MGMT 382 at Purdue University taught by Dr. Dejoie in Winter2015. Since its upload, it has received 366 views. For similar materials see Management Information Systems in Business, management at Purdue University.

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Date Created: 02/12/15
MGMT 382 Databases First Lecture Vasa Case Analysis Second Lecture II III IV V VI VII VIII Intro to Databases Before Databases Problems with Data Dependency Scrubbing it DBMS Advantages of DBMS Costs and Risks First Lecture II III IV V VASA Case Analysis a Includes notes from article not discussed in class Unclear or Missing Requirements Failure to manage Scope Changing scope can affect project plan Skipping minimizing SDLC phases Current Lecture VASA CASE Unclear or Missing Requirements a Missing or incorrectly during analysis phase i Communication lots of talking and no listening complicated because it was the 16005 super slow not really friends King assumes people know what he is talking about ii Shipbuilding 1 It is an art in the 16005 rather than a science 2 Used trial and error methodology 3 Master Shipwright dies stuff at this time is not written down so all of his thoughts and plans are lost ancient copyright system from spies passed down orally lots of illiteracy cant read or write doles out information over time to apprentices 4 King keeps changing things IV b Misdiagnosing problem in identi cation and selection phase addressing symptom instead of actual problem Failure to Manage Scope or Boundaries of Project a Scope Creep project expands beyond initial stated requirements i Starts as a regular ship then becomes a agship represents Sweden power fear in the eyes of the enemies the King s ability to win wars ii King originally wants 2 small 2 large ships 108 ft and 136 ft respectfully changes his mind during the implementation stage that he wants them to become medium 120 ft ships 2 this is extremely costly in the 16005 1 Why Because in order to make a 140 ft keel you need to nd an 140 ft tree also joints will crack with pressure and impact and in the 16005 its highly likely the ship will run into something no radar and GPS iii Guns get changed 24 lbs is the weight of the shot coming out of the gun gets very heavy why is this scope creep form 36D 60 because the king customer is ordering the change b Feature Creep developers add features that weren t part of the initial requirements i Sculptures 500 to impress king gets heavier and heavier ii 3 and 1 lb guns maybe they are llers because they only put 48 24 lb on the ship maybe they are spending the kings money because they can c Failure to de ne the scope of the project back in initiation and planning or identi cation and selection phase Changing Scope can Affect Project Plan a Plan is living breathing b Best worst average probable constant monitoring c Don t panic i Timeline was originally 3 ships in 5 years idealistically a perfect ship is 2 ships for every 23 years so already rushing then King adds a 4th ship 1 This doesn t work if you try to cut it in half either Skipping or minimizing SDLC phases a To cut time and or costs phases are cut short or eliminated b Testing is one of the rst things cut c Analysis and design phases also are victims i Cuts in adequate analysis lead to missing or unclear requirements ii Cuts in Design less optimal solution problems with development and implementation d VASA CASE cut corners with testing they didn t tell anyone they failed the test wasn t even good 30 men running across and it rocked and they never did a retest VI Changing Technology a Forward thinking b Cant stand still for too long c Must really understand you industry and eld well i VASA double decks for the gun deck they didn t understand at the time how it affected the center of gravity of the ship didn t offset raising the main deck so it was top heavy Vasa Syndrome very large scale project think about a time when a project failed Second Lecture I Introduction to Databases a Data meaningful facts text graphics images sound video segments b Information data processed to be useful in decision making c Database An organized collection of logically realted data i Her at Purdue student record library use corec use registrar advisor in krannert d Metadata description of data ll Before Data a File Processing b Disadvantages i Program data dependence all programs maintain metadata for each le they use each language expected to see data in a particular data 1 Mac vs WindowslEx reading someone elses notes that are in Spanish not useful to you ii Data Redundancy duplication of data different systemsprograms have separate copies of the same data result of programdata dependency 1 Duplication causes eventual problems can cause inconsistency iii Limit data Sharing 1 No centralized control of the data 2 Cant understand it not useful iv Lengthy development times 1 Programmers most design their own le formats v Excessive program maintenance 1 80 of information systems budget 2 EX employee s salary metadata has to be written the same so if it changes for every employee it changes for the metadata as data is changed Hunt down every place that the data gets changed c Problems with Data dependency i Each application programmer must maintain own data Needs to include code for metadata le iii Own processing routine iv Lack of coordination and central control v Nonstandard le formats EX Accounting department uses Fortran 72 5 gure salary in a data le the HR department uses Cobol so when they take the data le from Accounting problems will occur because each system reads the data differently I Scrubbing even you scrub the data in the previous example a Redundancy salary shows up in the Accounting department and HR waste of space to duplicate data causes maintenance issues b BGGEST PROBLEM when data changes in one le it usually causes inconsistency this compromises the data bad data bad information bad decisions bad action c Solution database i Central repository of shared data ii Data is managed by a controlling agent iii Stored in a standardized convenient form ll Requires a database Management System DBMS data storage and retrieval system which permits data to be stored nonredundanty while making it appear to the user as if data is wellintegrated lll Advantages a Program data independence metadata stored in DBMS so applications don t need to worry about data formats b Queries and updates managed to process data programs don t need to process data access routines i Results in increased app development maintenance productivity c Minimal Redundancy i Increase integrity and consistency d Improved data sharing different users get different views e Enforment of standards f Improved data quality constraints data validation rules g Security backup recover consistency disaster recovery is easier Costs and Risks a Up front costs i Installation management cost and complexity ii Conversion cots b Ongoing costs i Requires new specialized personnel ii Need for explicit backup and recovery c Organizational con ict i Old habits die hard ER Model Constructs a Entity instance person place object event concept row b Entity type collection of entities table c Attribute propertycharacteristics of an entity type eld d Relationship instance link between entities i Primary keyforeign key equivalencies 1 Relationship types link between entity types


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