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(Spring 2015) Instructor: Craig Duckett Lecture 03: Tuesday, April 14, 2015 Data vs. Information 1.

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Presentation on theme: "(Spring 2015) Instructor: Craig Duckett Lecture 03: Tuesday, April 14, 2015 Data vs. Information 1."— Presentation transcript:

1 (Spring 2015) Instructor: Craig Duckett Lecture 03: Tuesday, April 14, 2015 Data vs. Information 1

2 2 PHASE 1: DISCOVERY DUE: Tuesday, April 28 th, uploaded to Team Web Site and ZIPPED and uploaded to StudentRacker by Phase 1 Project Manager Phase 2: Design due Tuesday, May 19 th

3 3 The Team Project Five Phase Due Dates Phase 1: Discovery (200 Points) DUE TUESDAY, APRIL 28 Phase 2: Design (200 Points) DUE TUESDAY, MAY 19 Phase 3: Develop (200 Points) DUE THURSDAY, MAY 28 Phase 4: Distribute (200 Points) DUE TUESDAY, JUNE 9 Phase 5: Documentation (200 Points) DUE THURSDAY, JUNE 18

4 4 A Side Trip How Data is Stored in the Computer http://homepage.cs.uri.edu/book/binary_data/binary_data.htm Representation of Bitmapped Graphics Slide In an SQL database, we can store large files as BLOB s (Binary Large OBjects)

5 5 Database Design for Mere Mortals: Chapter 2 Summary Chapter 2: Design Objectives A logical design of the database is highly important. Wizards that help you create tables are of no real use if the database itself is designed improperly. Accuracy, integrity and consistency of data will be dependent upon a good design. Many problems can arise if there are design flaws, such as inaccurate retrieval of information. Objectives of Good Design: Supports required and ad hoc information retrieval Contains efficiently constructed tables Imposes data integrity at the field, table and relationship level Data must provide accurate and valid information that is meaningful to the organization The database structure should be easily modified for possible future growth Advantages of Good Design: Easy to modify and maintain the structure Easy to modify data Easy retrieval of information Easy to develop and build user applications

6 6 Database Design for Mere Mortals: Chapter 2 Summary There are three traditional design methods: A requirements analysis phase involves examining the business being modeled, interviewing users and management to assess the current system and to analyze future needs and determining information requirements for the businessas a whole A data modeling phase involves modeling the database structure itself by using a method such as entity relationship diagramming (ER diagramming). This provides a means of visually representing various aspects of the database structure, such as the tables, table relationships and relationship characteristics. The Normalization phase is the process of decomposing large tables into smaller tables in order to eliminate redundant data, duplicate data and avoid problems with inserting, modifying or deleting data. Table structures are tested against normal forms, which are a specific set of rules that can be used to test a table structure to be sure it is sound and free of problems. These normal forms are: First through Fifth Normal Forms, Boyce-Codd Normal Form and Domain/Key Normal Form.

7 Data vs. Information Data raw facts no context just numbers and text Information data with context processed data value-added to data summarized organized analyzed

8 Data vs. Information Data: 51215 Information: 5/12/15 - The date of your mid-term exam. $51,215 - The average starting salary of a computer science major. 51215 - Zip code of Snake's Navel, Arkansas

9 Data vs. Information Data 6.34 6.45 6.39 6.62 6.57 6.64 6.71 6.82 7.12 7.06 Information

10 Data  Information  Knowledge Data Information Summarizing the data Averaging the data Selecting part of the data Graphing the data Adding context Adding value

11 Data  Information  Knowledge Information Knowledge How is the info tied to outcomes? Are there any patterns in the info? What info is relevant to the problem? How does this info effect the system? What is the best way to use the info? How can we add more value to the info?

12 Information Systems Generic Goal: Transform Data  into  Information At the Core of an Information System is a Database (raw data).

13 Information Systems (TSP and PCS) Data doesn’t just "appear" Capturing Data is really the first step These systems help capture data but they also have other purposes (goals): 1. Transaction Processing Systems (TPS) 2. Process Control Systems (PCS) Discrete, Batch, Continuous

14 Capturing Data What kind of data is being captured? How is this data transformed into Information? How Is that information transformed into knowledge? How does that knowledge aid in decision-making?

15 Data Processing Recall that a basic system is composed of 5 components 1.Input 2.Output 3.Processing 4.Feedback 5.Control Typically processing helps transform data into information. InputOutput Processing Raw Data Information

16 Processing Summarizing Computing Averages Graphing Creating Charts Visualizing Data

17 A Scenario… Imagine it's 8:00 o'clock in the morning, and you're walking through a factory, that factory is in production, and you notice a pressure gauge on a pipe that shows 2200 psi. That is a piece of data. You go into the control room and there is a computer screen, and that screen is a graph of pressure, and you can see in fact that the pressure in that pipe is rising for rapidly. This is information provided to you as a time-series of data, data that is presented in such a way that makes sense, that tells you something. What is the knowledge you need right now? Presented with this information, what do you need to know right now? The key knowledge you need is what should I do? How should I respond? How should I react to this particular set of circumstances? Should I open a valve? Which valve should I open? Should I close a valve? Should I press the fire alarm and evacuate the factory because it's about to explore, or should I go and tell the director that we are at last on production and we can go and celebrate? If you know how to react, then you can make the correct decision. If you don't have that knowledge, then you're powerless. That's the difference between the data, the information, and the knowledge. The knowledge is the piece that allows you to make a decision. Now, where would you get that knowledge? Knowledge is the factor that allows you to take effective action, to make the correct decision with capability and know-how. Data Information Knowledge

18 18 Projects and the Team Formations Bothell Youth Court Wants a small database to hold names/cases/dates that can push a reminder when a particular case is scheduled to come up. Two people will be using it, both with administer access School of STEM (UW Bothell) Current using an Excel spreadsheet to enter and track information and would love to have a database to do this instead Project 3 Anybody have need of a database? Club? Recipes? Movies? Music? If so, list it on the index card (see next slide) Project 4 Anybody have need of a database? Club? Recipes? Movies? Music? If so, list it on the index card (see next slide)

19 19 Projects and Team Preferences Front of Index Card Your Name Project Preferences 1. Most Favorite... 4. Least Favorite Team Member Preferences Would LIKE to team with Would NOT want to team with Back of Index Card Skills Assessment Team Management Skills (0 – 5) Database Skills (0 – 5) SQL Skills (0 – 5) Design Skills (0 – 5) Project Idea Example: Club, recipes, films, music collection, etc

20 20 TEAMS http://www.glip.com/ https://www.trello.com/ Online Team Collaboration Programs (Free) http://www.moxtra.com/

21 21 A Look at Phase 1: Discovery DUE Tuesday, May 5 th, 2015 A Quick Look


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