1. © 2009 Prentice-Hall, Inc.1

2. 2 Technology in Action Chapter 11 Behind the Scenes: Databases and Information Systems

3. © 2009 Prentice-Hall, Inc.3 Chapter Topics Databases and their usesDatabases and their uses Database componentsDatabase components Types of databasesTypes of databases Database management systemsDatabase management systems Relational databasesRelational databases Data warehouses and data martsData warehouses and data marts Information systemsInformation systems Data miningData mining

4. © 2009 Prentice-Hall, Inc.4 Databases Collections of related dataCollections of related data Easily stored, sorted, organized, and queriedEasily stored, sorted, organized, and queried Turn data into informationTurn data into information Excel: create a simple list for 1 purposeExcel: create a simple list for 1 purpose Databases:Databases: –complex lists –Used for multiple purposes –College Admissions, Marketing Department, Housing

5. © 2009 Prentice-Hall, Inc.5 Advantages of Using Databases Store and retrieve large quantities of informationStore and retrieve large quantities of information Enable information sharingEnable information sharing Provide data centralizationProvide data centralization Promote data integrityPromote data integrity Allow for flexible use of dataAllow for flexible use of data

6. Database Management System Business Examples Customers Customers Employees Employees Products Products Orders Orders Invoices Invoices Personal Examples Mailing List DVD Collection Investments Household Inventory Recipes Goal: Retrieve and Report Information Means: Entering and Storing the Data

7. © 2009 Prentice-Hall, Inc.7 Disadvantages of Databases Complex to constructComplex to construct Time consumingTime consuming ExpensiveExpensive Privacy concernsPrivacy concerns

8. © 2009 Prentice-Hall, Inc.8 Database Terminology Field: Category of information, displayed in columnsField: Category of information, displayed in columns

9. © 2009 Prentice-Hall, Inc.9 Database Terminology RecordRecord –A group of related fields Record

10. © 2009 Prentice-Hall, Inc.10 Database Terminology TableTable –A group of related records Table

11. Primary Key Every table, should have a field designated or created to be a primary key Is A Unique identifier in your tableIs A Unique identifier in your table Examples:Examples: –Social Security Id –Patient Id –Doctor Id –An Auto number created by Access Ids help you identify patients with the same name and possibly living in the same home. John Johnson 610-555-4432 (FATHER)John Johnson 610-555-4432 (FATHER) John Johnson 610-555-4432 (SON)John Johnson 610-555-4432 (SON)

12. © 2009 Prentice-Hall, Inc.12 Database Terminology Primary keyPrimary key –A field value unique to a record (Student Id) Primary Key

13. © 2009 Prentice-Hall, Inc.13 Database Types Relational databasesRelational databases –Organize data in tables –Link tables to each other through their primary keys Object-oriented databases Object-oriented databases Multidimensional databasesMultidimensional databases

14. © 2009 Prentice-Hall, Inc.14 Database Management Systems (DBMS) Application software designed to capture and analyze dataApplication software designed to capture and analyze data Four main operations of a DBMS are:Four main operations of a DBMS are: 1.Creating databases and entering data 2.Viewing and sorting data 3.Extracting data 4.Outputting data

15. © 2009 Prentice-Hall, Inc.15 Creating Databases and Entering Data Create field names:Create field names: –Identify each type of data –Data dictionary

16. © 2009 Prentice-Hall, Inc.16 Database Terminology Data types: Type of data that can be stored in the fieldData types: Type of data that can be stored in the field

17. © 2009 Prentice-Hall, Inc.17 Creating Databases and Entering Data (cont.) Create individual records by:Create individual records by: –Key-in –Import –Input form

18. © 2009 Prentice-Hall, Inc.18 Data Validation ValidationValidation –Process of ensuring data entered into the database is correct (or at least reasonable) and complete Validation rulesValidation rules –Range check (age of student 13 – 99) –Completeness check (required fields like last name) –Consistency check (birth date < date enrolled) –Alphabetic/numeric checks (numbers only…)

19. © 2009 Prentice-Hall, Inc.19 Data Validation Example of completeness checkExample of completeness check

20. © 2009 Prentice-Hall, Inc.20 Viewing and Sorting Data Browse through recordsBrowse through records Sort records by field nameSort records by field name Before sort After sort

21. © 2009 Prentice-Hall, Inc.21 Extracting or Querying Data QueryQuery –A question or inquiry –Provides records based on criteria –Structured query language (SQL)

22. © 2009 Prentice-Hall, Inc.22 Outputting Data Reports:Reports: –Printed –Summary data reports Export dataExport data

23. © 2009 Prentice-Hall, Inc.23 Relational Database Operations Organize data into tablesOrganize data into tables Relationships are links between tables with related dataRelationships are links between tables with related data Common fields between tables need to existCommon fields between tables need to exist

24. © 2009 Prentice-Hall, Inc.24 Relational Database Operations Normalization of data (recording data once) reduces data redundancyNormalization of data (recording data once) reduces data redundancy Foreign key: The primary key of one table included in another to establish relationships with that other tableForeign key: The primary key of one table included in another to establish relationships with that other table

25. © 2009 Prentice-Hall, Inc.25 Data Storage Data warehousesData warehouses –A large scale repository of data –Organizes all the data related to an organization –Data is organized by subject

26. © 2009 Prentice-Hall, Inc.26 Source dataSource data –Internal sources Company databases, etc.Company databases, etc. –External sources Suppliers, vendors, etc.Suppliers, vendors, etc. –Customers or Web site visitors Clickstream dataClickstream data Populating Data Warehouses

27. © 2009 Prentice-Hall, Inc.27 Data Warehouse Process

28. © 2009 Prentice-Hall, Inc.28 Managing Data: Information Systems Information systemsInformation systems –Software-based solutions used to gather and analyze information Functions performed by information systems includeFunctions performed by information systems include –Acquiring data –Processing data into information –Storing data –Providing output options

29. © 2009 Prentice-Hall, Inc.29 Information Systems Categories Office support systemsOffice support systems Transaction processing systemsTransaction processing systems Management information systemsManagement information systems Decision support systemsDecision support systems

30. © 2009 Prentice-Hall, Inc.30 Office Support Systems (OSSs) Assist employees in day-to-day tasksAssist employees in day-to-day tasks Improve communicationsImprove communications Example: Microsoft OfficeExample: Microsoft Office Include e-mail, word processing, spreadsheet, database, and presentation programsInclude e-mail, word processing, spreadsheet, database, and presentation programs

31. © 2009 Prentice-Hall, Inc.31 Transaction Processing Systems (TPSs) Keeps track of everyday business activitiesKeeps track of everyday business activities Batch processingBatch processing Real-time processingReal-time processing

32. © 2009 Prentice-Hall, Inc.32 Management Information Systems (MISs) Provide timely and accurate information for managers to make business decisionsProvide timely and accurate information for managers to make business decisions Detail report: –Transactions that occur during a period of time Summary report: –Consolidate detailed data Exception report: –Show unusual conditions

33. © 2009 Prentice-Hall, Inc.33 Decision Support Systems (DSSs) Help managers develop solutions for specific problemsHelp managers develop solutions for specific problems

34. © 2009 Prentice-Hall, Inc.34 Data Mining Process by which great amounts ofdata are analyzed and investigatedProcess by which great amounts of data are analyzed and investigated Objective is to spot patterns or trends within the dataObjective is to spot patterns or trends within the data

35. © 2009 Prentice-Hall, Inc.35 Data Mining Methods ClassificationClassification –Define data classes EstimationEstimation –Assign a value to data Affinity grouping or association rulesAffinity grouping or association rules –Determine which data goes together ClusteringClustering –Organize data into subgroups Description and visualizationDescription and visualization –Get a clear picture of what is happening

36. Let’s Get Started ? These questions may be on Access Test ? 1.Score Keeper 2.½ Class write their name on a piece of paper 3.Pick 5-6 teams 4.Name of team – a favorite TV character 5.Help Desk – Understanding Databases 6.Multiple Choice and Fill in the Blanks 7.Help Desk – Using Databases 8.Sound Bytes and answer questions 9.On-Line Study Guide?