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Transcript
Unit 1
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Introduction
Syllabus
Questions
Database Systems Overview
This course is an introduction to database management
systems. Students will use a relational database
management system to create and maintain a
database. Students will create filters, sorts, queries, forms,
and reports. Emphasis will be placed on the skills needed to
meet user requirements. By the end of this course, you will:
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1. Describe underlying database theories and concepts.
2. Discuss database integration.
3. Create relational databases with multiple tables.
4. Create reports.
5. Write queries.
6. Formulate a logical solution to a problem.
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Nathan Botts, PhD Information Systems &
Technology, Claremont Graduate Univeristy
Living in Rhode Island
Westat - Health IT Researcher and CTO of
HealthATM
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Seminars = Thursdays 9pm EST
Projects are due Tuesday 11:59 pm EST of
their assigned Unit.
All course projects submitted on time will be
graded within five days of their due date (the
Sunday of the following unit).
Title: Microsoft Office Access 2010:
Comprehensive Concepts and Techniques
Author:
Publisher:
Shelly, Cashman, & Pratt
Course Technology
ISBN:
0-538-74862-1
Files:
Located in Doc Sharing
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Read Chapter 1
DB – Topic #1 and #2
And that’s it!
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Post a minimum of three posts
per discussion question. One
initial response and two replies
to your classmates
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Posting on a minimum of three
different days, for example:
Wednesday, Friday and Monday
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The first post must be made by
Saturday.
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Any organized collection of data
A collection of similar data
Examples of databases:
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Telephone book white pages
T.V. Guide
Airline reservation system
Motor vehicle registration records
Papers in your filing cabinet
Files on your computer hard drive
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Data
 Can be defined in many ways
 IS defines data as unprocessed information
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Information
 Data that have been organized and communicated in a
coherent and meaningful manner
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Knowledge
 Knowledge; information evaluated and organized so that
it can be used purposefully
Data is converted into information, and
information is converted into knowledge
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We collect data
Information is harvested from data
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Many companies are good at collecting data
Fewer are good at harvesting information
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To transform
Data
Information
Knowledge
Action
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Keep records of our:
 Clients
 Staff
 Volunteers
To keep a record of activities
and interventions
Keep sales records
Develop reports
Perform research
Longitudinal tracking
(Say what?)
Fields (columns)
Records
(rows)
Anderson
Benson
Casserly
Drummond
Thomas A 123 Marine View Dr.
Karen
C 1300 California Ave
Rick
W 12492 Rd 19
Lynn
M 12059 30th Ave W
237-1234
237-1098
342-0502
931-1105
Table
Field
(the columns in a table)
•
•
Smallest unit of information in a table
Sometime called “attributes”
•
Phone book: an individual’s first name, last name, middle
initial, street address, and telephone number
Record
(the rows in a table)
•
All related fields are collectively called a record
Table
•
A collection of records is a data table
Database Management
System (DBMS)
•
All the related tables, queries, data entry and edit forms,
reports, macros and VBA modules constitute a database
•
Phone book: all fields for one individual create a record
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Software data tools to:
 Store (tables)
 Organize (sort)
 Add, modify or delete
 Ask questions (queries)
 Produce forms and reports
▪ Summarizing
▪ Displaying details
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Toolbox is a good analogy
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Microsoft Access
Structured Query Language (SQL)
 Microsoft SQL Server
 Oracle
 MySQL
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FileMaker Pro
Lotus Notes
New database technologies (MapReduce)
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Operational databases
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Used to track and assist in the daily “business” activities
Data typically changes frequently reflecting activities occurring over time
Examples
▪
▪
▪
▪
▪
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H/R systems
Mailing lists
Inventory management programs
Accounting systems (including programs like Quicken and QuickBooks)
Point of sale systems (cash registers)
Analytical databases
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Tend to be more static including larger amounts of historical data
Data is then analyzed (processed) looking for patterns or trends
Often support the strategic activities of an organization
Goal may be
▪ Predict the future
▪ Summarize historical data
▪ Prove historical assumptions
▪ Did a pattern of discrimination occur
▪ What is the price elasticity for a product line
▪ Developing industry averages
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Operational databases can contain analytical components
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Flat-File Database
 All relevant data in a single table, or series of unrelated tables
 Work best for small quantities of data; where viewing and sorting the
data in a single list does not create a time-consuming task
 Typically a person’s first databases
 Example: Excel spreadsheet or Word data list file
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Relational Database
 Provide a solution to data entry redundancy problems
 Linked through common fields (columns) with exactly the same data
 Tables linked together can be queried as if one table
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Weaknesses common to flat-file systems
 Note the duplicate information in the table
 Inconsistencies in the way Supervisor Names are entered
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Can be divided into two categories
 Desktop databases
▪ Oriented toward single-user applications
▪ Reside on standard personal computers
 Client / Server databases
▪ Contain mechanisms to
▪ Ensure the reliability and consistency of data
▪ Data security
▪ Oriented toward multi-user applications
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Will vary with the organization
At a minimum, should answer the following questions:
 How many records will be stored and for how long?
 Who will be using the database?
▪ What tasks will they perform?
 How often will the data be modified?
▪ Who will make these modifications?
 Who will be providing IT support for the database?
 What hardware is available?
▪ Is there a budget for purchasing additional hardware?
 Who will be responsible for maintaining the data?
 Will data access be offered over the Internet?
▪ If so, what level of access should be supported?
 What level of security is needed and how will it be enforced?