1. Organizing Data and Information AD660 – Databases, Security, and Web Technologies Marcus Goncalves Spring 2013

2. Introduction  Database: an organized collection of data  Database management system (DBMS): group of programs to manage database –Manipulates database –Provides an interface between database and the user of the database and other application programs  Database administrator (DBA): skilled IS professional who directs all activities related to an organization’s database

3. Data Management  Without data and the ability to process it, an organization could not successfully complete most business activities  Data consists of raw facts  For data to be transformed into useful information, it must first be organized in a meaningful way

4. The Hierarchy of Data  Bit (a binary digit): a circuit that is either on or off  Byte: eight bits  Character: basic building block of information –Each byte represents a character –Can be an uppercase letter, lowercase letter, numeric digit, or special symbol  Field: typically a name, number, or combination of characters that describes an aspect of a business object or activity

5. The Hierarchy of Data (continued)  Record: a collection of related data fields  File: a collection of related records  Database: a collection of integrated and related files  Hierarchy of data: bits, characters, fields, records, files, and databases

6. The Hierarchy of Data (continued)

7. Data Entities, Attributes, and Keys  Entity: a generalized class of people, places, or things (objects) for which data is collected, stored, and maintained  Attribute: characteristic of an entity  Data item: value of an attribute  Key: field or set of fields in a record that is used to identify the record  Primary key: field or set of fields that uniquely identifies the record

8. Data Entities, Attributes, and Keys (continued)

9. The Database Approach  Traditional approach to database management: separate data files are created for each application –Results in data redundancy (duplication) –Data redundancy conflicts with data integrity  Database approach to database management: pool of related data is shared by multiple applications –Significant advantages over traditional approach

10. The Database Approach (continued)

14. Data Modeling and the Relational Database Model  When building a database, consider: –Content: What data should be collected, at what cost? –Access: What data should be provided to which users and when? –Logical structure: How should data be arranged to make sense to a given user? –Physical organization: Where should data be physically located?

15. Data Modeling (continued) An Entity-Relationship (ER) Diagram for a Customer Order Database

16. The Relational Database Model  Relational model: all data elements are placed in two- dimensional tables (relations), which are the logical equivalent of files  In the relational model –Each row of a table represents a data entity –Columns of the table represent attributes –Domain: the allowable values for data attributes

17. The Relational Database Model (continued) A Relational Database Model

18. Manipulating Data  Selecting: eliminates rows according to criteria  Projecting: eliminates columns in a table  Joining: combines two or more tables  Linking: relates or links two or more tables using common data attributes

19. Manipulating Data (continued) Linking Data Tables to Answer an Inquiry

20. Database Management Systems (DBMS)  Interface between: –Database and application programs –Database and the user  Creating and implementing the right database system ensures that the database will support both business activities and goals  DBMS: a group of programs used as an interface between a database and application programs or a database and the user

21. Overview of Database Types  Flat file –Simple database program whose records have no relationship to one another  Single user –Only one person can use the database at a time –Examples: Access, FileMaker, and InfoPath  Multiple user –Allows dozens or hundreds of people to access the same database system at the same time –Examples: Oracle, Sybase, and IBM

22. Creating and Modifying the Database (continued) Figure 3.10: Using a Data Definition Language to Define a Schema

23. Storing and Retrieving Data

24. Database Administration  Database administrator (DBA): directs or performs all activities to maintain a database environment –Designing, implementing, and maintaining the database system and the DBMS –Establishing policies and procedures –Employee training

25. Popular Database Management Systems  Popular DBMSs for end users: Microsoft Access and FileMaker Pro  Entire market includes databases by IBM, Oracle, and Microsoft  Examples of open-source database systems: PostgreSQL and MySQL  Many traditional database programs are now available on open-source operating systems

26. Data Warehouses, Data Marts, and Data Mining  Data warehouse: collects business information from many sources in the enterprise  Data mart: a subset of a data warehouse  Data mining: an information-analysis tool for discovering patterns and relationships in a data warehouse or a data mart

27. Data Warehouses, Data Marts, and Data Mining (continued) Elements of a Data Warehouse

28. Business Intelligence  Business intelligence (BI): gathering the right information in a timely manner and usable form and analyzing it to have a positive impact on business –Turns data into useful information that is then distributed throughout an enterprise

29. Business Intelligence (continued)  Competitive intelligence: aspect of business intelligence limited to information about competitors and the ways that knowledge affects strategy, tactics, and operations  Counterintelligence: steps an organization takes to protect information sought by “hostile” intelligence gatherers

30. Distributed Databases  Distributed database –Data may be spread across several smaller databases connected via telecommunications devices –Corporations get more flexibility in how databases are organized and used  Replicated database –Holds a duplicate set of frequently used data