Database Management Essentials

Objectives

• Learn the difference between data and information
• Understand what a database is, its types, and its value in decision making
• Appreciate the importance of database design
• Study how modern databases evolved from file systems
• Identify flaws in file system data management
• Learn about the main components of a database system and the functions of a database management system (DBMS)

Information Management

• Involves six related activities: identification of information needs, acquisition and creation of information, analysis and interpretation of information, organization and storage of information, information access and dissemination, and information use and archiving
• Is the management of organizational processes and systems that acquire, create, organize, distribute, and use information

DIKAR Model

• Gives a strong clue as to the layers involved in aligning technology and organizational strategies
• Recognizes that information management is an investment that must deliver meaningful results

Data vs. Information

• Data refers to raw facts about a topic or item
• Information is the result of combining, comparing, and performing calculations on data
• Data gives meaning to the raw facts through processing

File System and Data Processing

• File systems have structural and data dependence, which makes it difficult to change file structure or data storage characteristics
• Data dependence affects data access, and data storage characteristics do not affect data access in data independence
• Logical data format is how humans view data, while physical data format is how computers work with data
• File system structure makes it difficult to combine data from multiple sources, leading to data redundancy and security breaches
• Data redundancy leads to data inconsistency, data anomalies, and update anomalies

Problems with File System Data Processing

• Structural dependence: access to a file is dependent on its own structure
• Data dependence: data access changes when data storage characteristics change
• Data redundancy: same data stored unnecessarily in different places
• Data inconsistency: different and conflicting versions of the same data occur at different places
• Data anomalies: abnormalities when all changes in redundant data are not made correctly
• Update anomalies: insertion, deletion, and modification anomalies occur when data is not updated consistently