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Unit 1.  Introduction  Syllabus  Questions  Database Systems Overview.

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Presentation on theme: "Unit 1.  Introduction  Syllabus  Questions  Database Systems Overview."— Presentation transcript:

1 Unit 1

2  Introduction  Syllabus  Questions  Database Systems Overview

3 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:  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.

4  Nathan Botts, PhD Information Systems & Technology, Claremont Graduate Univeristy  Living in Rhode Island  Westat - Health IT Researcher and CTO of HealthATM

5  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).

6 Title: Microsoft Office Access 2010: Comprehensive Concepts and Techniques Author: Shelly, Cashman, & Pratt Publisher: Course Technology ISBN: 0-538-74862-1 Files: Located in Doc Sharing

7  Read Chapter 1  DB – Topic #1 and #2  And that’s it!

8  Post a minimum of three posts per discussion question. One initial response and two replies to your classmates  Posting on a minimum of three different days, for example: Wednesday, Friday and Monday  The first post must be made by Saturday.

9  Any organized collection of data  A collection of similar data  Examples of databases:  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

10  Data  Can be defined in many ways  IS defines data as unprocessed information  Information  Data that have been organized and communicated in a coherent and meaningful manner  Knowledge  Knowledge; information evaluated and organized so that it can be used purposefully Data is converted into information, and information is converted into knowledge

11  We collect data  Information is harvested from data  Many companies are good at collecting data  Fewer are good at harvesting information

12 Data Information Knowledge Action To transform

13  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?)

14 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 Phone book: all fields for one individual create 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

15  Software data tools to:  Store (tables)  Organize (sort)  Add, modify or delete  Ask questions (queries)  Produce forms and reports ▪ Summarizing ▪ Displaying details  Toolbox is a good analogy

16  Microsoft Access  Structured Query Language (SQL)  Microsoft SQL Server  Oracle  MySQL  FileMaker Pro  Lotus Notes  New database technologies (MapReduce)

17  Operational databases  Used to track and assist in the daily “business” activities  Data typically changes frequently reflecting activities occurring over time  Examples ▪ H/R systems ▪ Mailing lists ▪ Inventory management programs ▪ Accounting systems (including programs like Quicken and QuickBooks) ▪ Point of sale systems (cash registers)  Analytical databases  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  Operational databases can contain analytical components

18  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  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

19  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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25  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

26  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?

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