Database Management Chapter 1

Chapter 1: The Database Environment and Development Process

• This chapter covers the database environment and development process, focusing on database management essentials.

• Learning objectives include defining terms, identifying limitations of file processing, explaining advantages of databases, identifying database costs and risks, listing database components, and more.

• Databases are structured collections of logically related data, representing meaningful objects and events.

• Data can be structured (numbers, text, dates) or unstructured (images, videos, documents).

• Information is processed data, increasing knowledge in the user.

• Metadata describes the properties and context of user data.

• Data context helps users understand data.

• Figure 1-1a shows a class roster, highlighting data in context.

• Figure 1-1b illustrates summarized data, presenting it graphically for use in decision-making and interpretation.

• Table 1-1 demonstrates metadata example for a class roster. This provides information on data characteristics like data types, length, minimum and maximum values, and descriptions.

• Disadvantages of file processing include program-data dependence, duplication of data, limited data sharing, lengthy development times, excessive program maintenance.

• File processing has issues with data dependency where each application handles its own data, lacking central control and using non-standard formats.

• Data redundancy wastes storage space and leads to inconsistencies.

• The database approach offers a centralized repository of shared data, managed by a controlling agent, stored in a standardized format. This necessitates a database management system (DBMS).

• DBMSs manage data resources like operating systems manage hardware resources. A DBMS manages data resources, providing controlled access to user databases.

• Benefits of the database approach include program-data independence, planned data redundancy, improved data consistency, improved data sharing, increased application development productivity, enforcement of standards, improved data quality, accessibility and responsiveness, reduced maintenance, and improved decision support.

• Costs and risks associated with databases include personnel costs, installation and management complexity, conversion costs, backup and recovery needs, and organizational conflicts.

• Data models, graphical systems capturing data nature and relationships, are important.

• Enterprise Data Models provide a high-level overview, while Project Data Models offer a more detailed view. Entities are nouns describing people, places, objects, events, composed of attributes.

• Relationships exist between entities, often one-to-many (1:M) or many-to-many (M:N). Relational databases involve tables representing entities, with primary and foreign keys representing relationships.

• Figure 1-3 compares enterprise and project-level data models, highlighting relationships, such as "Is Placed By", "Contains", "Is Contained In," and "Has".

• One-to-many and many-to-many relationships between entities are also discussed.

• Figure 1-4 shows an enterprise model of the various components discussed in figure 1-3

• The components of a database environment include CASE tools, repositories, database management systems (DBMSs), databases, application programs, and User Interfaces.

• Data and database administrators, system developers, and end-users are also crucial parts of the environment.

• The Enterprise Data Model is the first step in database development. It specifies data scope and general content, offering a high-level abstraction of organizational data. It's depicted in an Entity-Relationship diagram.

• Figure 1-6 illustrates a business function-to-data entity matrix.

• Database development approaches include the System Development Life Cycle (SDLC) and Prototyping. SDLC is detailed and time-consuming. Prototyping offers a rapid application development (RAD) approach, prioritizing working software, customer collaboration, and responsiveness to change.

• The Systems Development Life Cycle (SDLC), a well-planned process, is detailed, time-consuming, but comprehensive for database and Information Systems development.

• The steps within SDLC include Planning, Analysis, Logical Design, Physical Design, Implementation, and Maintenance.

• Agile software development emphasizes individuals, interactions, working software, customer collaboration, and responding to change.

• A database schema combines enterprise model and detailed user views, categorized as External (User Views, top-down and bottom-up), Conceptual, and Internal (Logical and Physical).

• Figure 1-9 visually illustrates a three-schema architecture.

• Figure 1-10a shows evolution of database technologies over time.

• Figure 1-10b displays database architectures, including hierarchical, network, relational, object-oriented, and multidimensional models.

• Figure 1-11 illustrates a two-tier database architecture with a local area network.

• Figure 1-12 illustrates a three-tiered client/server database architecture.

• Enterprise resource planning (ERP) is a type of database application that integrates all enterprise functions (manufacturing, finance, sales, marketing, inventory, accounting, human resources).

• Data warehousing creates integrated decision support systems from operational databases.

• Figure 1-13 provides a graphical illustration of a computer system.

• There are different categories of applications with varying numbers of users and database sizes, as summarized in Table 1-5.

Explore the fundamentals of databases in this quiz focused on Chapter 1: The Database Environment and Development Process. Understand key concepts such as the definitions, limitations of file processing, advantages of databases, and the role of metadata in data management. Test your knowledge of database components and their significance in today’s information systems.