Managing Data Resources Chapter 7 Managing Data Resources

Objectives Why do businesses have trouble finding the information they need in their information systems? How does a database management system help businesses improve the organization of their information?

Objectives How do the principal types of database models affect the way businesses can access and use information? What are the managerial and organizational requirements of a database environment? What new tools and technologies can make databases more accessible and useful?

Management Challenges Organizational obstacles to a database environment Cost/benefit considerations

Organizing Data in a Traditional File Environment File Organization Terms and Concepts Bit: Smallest unit of data; binary digit (0,1) Byte: Group of bits that represents a single character Field: Group of words or complete number Record: Group of related fields File: Group of records of the same type

Organizing Data in a Traditional File Environment File Organization Terms and Concepts Database: Group of related files Entity: Person, place, thing, or event about which information must be kept Attribute: A piece of information describing a particular entity Key field: Field that uniquely identifies every record in a file

Organizing Data in a Traditional File Environment The data hierarchy Figure 7-1

Organizing Data in a Traditional File Environment Entities and attributes Figure 7-2

Organizing Data in a Traditional File Environment Problems with the Traditional File Environment Data redundancy Program-data dependence Lack of flexibility Poor security Lack of data-sharing and availability

Organizing Data in a Traditional File Environment Traditional file processing Figure 7-3

The Database Approach to Data Management Database Management Systems Database Collection of centralized data Controls redundant data Data stored so as to appear to users in one location Services multiple application

The Database Approach to Data Management The contemporary database environment Figure 7-4

The Database Approach to Data Management Database Management Systems Database Management System (DBMS) Creates and maintains databases Eliminates requirement for data definition statements Acts as interface between application programs and physical data files Separates logical and physical views of data

The Database Approach to Data Management Database Management Systems Three Components to a DBMS Data definition language: Formal language programmers use to specify structure of database Data manipulation language: For extracting data from database, e.g. SQL Data dictionary: Tool for storing, organizing definitions of data elements and data characteristics

The Database Approach to Data Management Sample data dictionary report Figure 7-5

The Database Approach to Data Management Database Management Systems How a DBMS Solves Problems of a Traditional File Environment Reduces data redundancy Eliminates data inconsistency Uncouples programs from data Increases access and availability of data Allows central management of data, data use, and security

The Database Approach to Data Management Types of Databases Relational DBMS Represents data as two-dimensional tables called relations Relates data across tables based on common data element Examples: DB2, Oracle, MS SQL Server

The Database Approach to Data Management The relational data model Figure 7-6

The Database Approach to Data Management Types of Databases Three Basic Operations in a Relational Database Select: Creates subset of rows that meet specific criteria Join: Combines relational tables to provide users with information Project: Enables users to create new tables containing only relevant information

The Database Approach to Data Management The three basic operations of a relational DBMS Figure 7-7

The Database Approach to Data Management Types of Databases Hierarchical DBMS Older system presenting data in tree-like structure Models one-to-many parent-child relationships Found in large legacy systems requiring intensive high-volume transactions: Banks; insurance companies Examples: IBMs IMS

The Database Approach to Data Management A hierarchical database for a human resources system Figure 7-8

The Database Approach to Data Management Types of Databases Network DBMS Older logical database model Models many-to-many parent-child relationships Example: Student – course relationship: Each student has many courses; each course has many students

The Database Approach to Data Management The network data model Figure 7-9

The Database Approach to Data Management Types of Databases Disadvantages of Hierarchical and Network DBMS Outdated Less flexible compared to RDBMS Lack support for ad-hoc and English language-like queries

The Database Approach to Data Management Types of Databases Object-Oriented Databases (OODBMS) Stores data and procedures as objects Better able to handle graphics and recursive data Data models more flexible Slower than RDBMS Hybrid: object-relational DBMS

Creating a Database Environment Designing Databases Two Design Exercises in Creating Database Conceptual (logical) design: Abstract model of database from business perspective Physical design: How the database is actually arranged on direct access storage devices

Creating a Database Environment Designing Databases Conceptual Database Design Identifies relationships between data elements Identifies most efficient way to group data elements Identifies redundant data elements Identifies grouping of data elements needed for specific applications

Creating a Database Environment Designing Databases Entity-Relationship Diagram A methodology for documenting databases that illustrates the relationship between various elements in the database Normalization The process of creating small, stable, and adaptive data structures from complex groups of data when designing a relational database

Creating a Database Environment An entity-relationship diagram Figure 7-10

Creating a Database Environment An unnormalized relation for ORDER Figure 7-11

Creating a Database Environment A normalized relation for ORDER Figure 7-12

Creating a Database Environment Distributing Databases Distributed Database Partitioned or replicated to more than one location Increases service and responsiveness Reduces vulnerability of single, massive central site Depend on telecommunication lines Pose security risks through distribution of sensitive data Central data must be updated or justified with local data

Creating a Database Environment Distributed databases Figure 7-13

Creating a Database Environment Key organizational elements in the database environment Figure 7-14

Creating a Database Environment Management Requirements for Database Systems Data Administration Develop information policy Define information requirements Plan for data Oversee logical database design and database dictionary development Monitor use of information

Creating a Database Environment Management Requirements for Database Systems Data Planning and Modeling Methodology Enterprise-wide planning for data Identify key entities, attributes, and relationships that constitute the organization’s data

Creating a Database Environment Management Requirements for Database Systems Database Technology, Management, and Users Databases require DBMS software and staff Database design group defines and organizes structure and content of database Database administration: establish physical database, logical relations, access rules

Multidimensional Data Analysis Database Trends Multidimensional Data Analysis Online Analytical Processing (OLAP) Multidimensional data analysis Enables users to view the same data in different ways using multiple dimensions Each aspect of information – product, price, region – represents a different dimension

Multidimensional data model Database Trends Multidimensional data model Figure 7-15

Data Warehouses and Datamining Database Trends Data Warehouses and Datamining Data warehouse: Stores current and historical data for reporting, analysis Data mart: Subset of data warehouse with summary of data for specific users Datamining: Techniques to find hidden patterns, relationships in large pools of data to infer rules for predicting future trends

Components of a data warehouse Database Trends Components of a data warehouse Figure 7-16

Data Warehouses and Datamining Database Trends Data Warehouses and Datamining Benefits of Data Warehouses Improved information and accessibility Ability to model and remodel data Enable access to data without affecting performance of underlying operational legacy systems

Data Reveal New Sales Opportunities Database Trends Window on Management Data Reveal New Sales Opportunities How did the use of data warehouses and datamining help management at these companies make better decisions? What value do these systems provide?

Data Warehouses and Datamining Database Trends Data Warehouses and Datamining Hypermedia database Organizes data as network of nodes Links nodes in pattern specified by user Supports text, graphic, sound, video and executable programs

Database Trends A hypermedia database Figure 7-17

Linking Internal Databases to the Web Database Trends Databases and the Web Linking Internal Databases to the Web Database server: Hosts DBMS Receives SQL requests Provides required data Middleware: Works between Web server and DBMS to take requests Handles connectivity to database Can be application server or CGI scripts

Linking internal databases to the Web Database Trends Linking internal databases to the Web Figure 7-18

Advantages to Web Access to Databases Database Trends Databases and the Web Advantages to Web Access to Databases Browser software easy to use; little training Web interface requires no changes to internal database Costs less than custom interfaces

Web Access for Royal Bank Statements Database Trends Window on Technology Web Access for Royal Bank Statements Pays Off What are the business benefits of providing a Web interface for the Bankbook Reconstruct application? What value does this application provide the company and its customers?

Database Woes Plague Homeland Security and Law Enforcement Chapter 7 Case Study Database Woes Plague Homeland Security and Law Enforcement Briefly summarize why it is important to connect much of the data in many of the federal, state, and local information systems. Describe the major data management problems in bringing these data together. Describe the management, organization, and technology issues that need to be addressed to make these data easily available to those who need it.

Database Woes Plague Homeland Security and Law Enforcement Chapter 7 Case Study Database Woes Plague Homeland Security and Law Enforcement Suppose you are a consultant to the federal government. Based on what you have read in this chapter, suggest and describe three approaches you might recommend for making this massive amount of data easily and quickly available when needed.