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Chapter 4: Database Management. Databases Before the Use of Computers Data kept in books, ledgers, card files, folders, and file cabinets Long response.

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Presentation on theme: "Chapter 4: Database Management. Databases Before the Use of Computers Data kept in books, ledgers, card files, folders, and file cabinets Long response."— Presentation transcript:

1 Chapter 4: Database Management

2 Databases Before the Use of Computers Data kept in books, ledgers, card files, folders, and file cabinets Long response time Labor-intensive Often incomplete or inaccurate

3 Key Database Issues and Activities Entering and Querying Data Creating Database Reports Maintaining Data

4 Entering and Querying Data Use a form for data entry Use queries to retrieve information –Structured Query Language (SQL) –Query by example (QBE)

5 Creating Database Reports Report –A compilation of data organized and produced in printed format DBMS packages include a report writer Graphics can be added Can be automatically updated by linking to data

6 To Efficiently Maintain Data Model the data Select a physical structure –Hierarchical –Network –Relational Normalization process –Incl. Update / insert / delete procedures

7 Data Modeling Ensures all needed data represented in the correct form, Identifies all the relationships that exists among data: “Associations”, Communicates assumptions about the data and relationships with the users of data.

8 Associations Relationships among the entities in the data structures Three types –One-to-one –One-to-many –Many-to-many

9 - U.S. Airways - The fifth largest airline in America, U.S. Airways--with 2500 jet flights per day--is using an IBM database system to better manage its in-flight meal and video services. By analyzing upgrade, no- show, and cancellation patterns, U.S. Airways can more accurately predict how many meals are needed on each flight. … (page 2-92)

10 Selecting a physical structure in which to store the data Hierarchical Network Relational

11 The Hierarchical Model

12 The Network Model

13 The Relational Model

14 Normalization A technique used to make complex databases more efficient Break one large table into several smaller tables –Eliminates all repeating groups in records –Eliminates redundant data

15 Redundant Data

16 Normalized Data

17 Logical vs. physical representation of data The same “number” can be: –An invoice number in sales –A billing number in accounting –A picking number in warehouse –A delivery ticket number in distribution

18 Recent Developments Databases and Client-Server Computing –Server holds the actual database –Clients hold software to work with the database

19 Client/Server Database

20 Recent Developments Object-Oriented Databases (OODBs) –Treat tables, queries, etc., as reusable objects

21 Recent Developments Data Mining (On-Line Analytical Processing) –Drill down from summary data to detailed data –Data Warehouses/Data Marts Integrates many large databases into one repository Table 4.3 Sample industry uses of data warehousing (adapted from: Boar, 1998).

22 Recent Developments Linking Web Site Applications to Organizational Databases –Users have Web view to organizational database –Improves customer contact and service –Adds security as a concern

23 - CNN Interactive - An example of successfully linking a large corporate database with a Web interface can be found at CNN Interactive. CNN Interactive provides a free, online custom news service to hundreds of thousands of subscribers around the world. … (page 2-109)

24 Effective Management of Databases Database Administrator (DBA) –Responsible for the development and management of an organization’s databases Works with systems analysts on design Works with users and managers on managerial and organizational issues Responsible for implementing security features

25 Key Terms Databases: Collections of related data organized in a way that facilitates data searches. Database management systems: Software applications with which you can create, store, organize, and retrieve data for one or many databases. Entity: Things about which we collect data, such as people, courses, customers, or products.

26 Tables: Collections of related records about an entity type, where each row is a record and each column is a field. Field: Individual pieces of information about an entity, such as a person’s last name or social security number, stored in a database cell. Record: A collection of related fields about an entity, usually displayed as a row in a database.

27 Form: A collection of blank entry boxes, each representing a field, which is used to enter information into a database. Querying: Requesting information from a database. Structured Query Language (SQL): The most common set of commands used to request information from a database. Query by example (QBE): A capability of a DBMS to enable us to request data by simply providing a sample or a description of the types of data we would like to see.

28 Report: A compilation of data that is organized and produced in a printed format. Data model: A representation of entities and their relationships in the real world. Primary key: A field included in a database that can be used to uniquely identify each instance of an entity. Data type: Format for the data stored within a field.

29 Data dictionary: A repository that describes data types, uses, storage requirements, rules that affect data, and so on. Hierarchical database model: A DBMS approach in which entities are described in a parent-child relationship. Network database model: A DBMS approach in which entities can have multiple parent-child relationships.

30 Relational database model: A DBMS approach in which entities are presented as two- dimensional tables that can be joined together with common columns Normalization: A process of making data structures simple and clear Client/server architecture: A distributed processing system in which a client application that needs data or software gets it from a server that is a source for some or all of the needed data or software.

31 Database server: a powerful computer that contains the database and responds to queries from client computers in a client/server application. Object-oriented databases: Database management systems that follow the object- oriented approach of reusable objects, encapsulation, inheritance, and so on. Data mining: Sorting and analyzing information stored in organizational databases

32 Data warehouses: Repositories integrating multiple large databases and other informational sources in a single repository or access point that is suitable for direct querying, analysis, or processing. Data marts: Small-scale data warehouses that contain a sub-set of the data for a single aspect of a company’s business (for example, finance, inventory, or personnel). Database administrator: Person responsible for the development and management of the organization’s databases.

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