5.1 Managing Data
Difficulties in managing data:
• Amount of data increasing exponentially
• Data are scattered throughout organizations and collected by many individuals using various methods and devices.
• Data come from many sources.
• Data security, quality, and integrity are critical.
Data governance: is an approach to managing information across an entire organization.
Master data management: is a process that spans all of an organization’s business processes and applications.
Master data: are a set of core data that span all of an enterprise’s information systems.
5.2 The Database Approach
*Database management system (DBMS) minimizes the following problems:
Data redundancy: The same data are stored in many places.
Data isolation: Applications cannot access data associated with other applications.
Data inconsistency: Various copies of the data do not agree.
*DBMS's maximize the following issues:
Data security: Keeping the organization’s data safe from theft, modification, and/or destruction.
Data integrity: Data must meet constraints (e.g., student grade point averages cannot be negative).
Data independence: Applications and data are independent of one another. Applications and data are not linked to each other, meaning that applications are able to access the same data.
*Data Hierarchy:
A bit is a binary digit, or a “0” or a “1”.
A byte is eight bits and represents a single character (e.g., a letter, number or symbol).
A field is a group of logically related characters (e.g., a word, small group of words, or identification number).
A record is a group of logically related fields (e.g., student in a university database).
A file is a group of logically related records.
A database is a group of logically related files.
*Designing the Database:
Data model: The data model is a diagram that represents the entities in the database and their relationships.
Entity: An entity is a person, place, thing, or event about which information is maintained. A record generally describes an entity.
Attribute: An attribute is a particular characteristic or quality of a particular entity.
Primary key: The primary key is a field that uniquely identifies a record.
Secondary keys: Secondary keys are other field that have some identifying information but typically do not identify the file with complete accuracy.
*Entity-Relationship Modeling:
Database designers plan the database design in a process called entity-relationship (ER) modeling. ER diagrams consist of entities, attributes and relationships.
Entity classes: Entity classes are groups of entities of a certain type.
Instance: An instance of an entity class is the representation of a particular entity.
Identifiers: Entity instances have identifiers, which are attributes that are unique to that entity instance.
5.3 Database Management Systems
Database management system (DBMS): A database management system is a set of programs that provide users with tools to add, delete, access, and analyze data stored in one location
Relational database model: The relational database model is based on the concept of two-dimensional tables:
- Structured Query Language (SQL): Structured query language allows users to perform complicated searches by using relatively simple statements or keywords.
- Query by Example (QBE): Query by example allows users to fill out a grid or template to construct a sample or description of the data he or she wants.
*Normalization:
Normalization is a method for analyzing and reducing a relational database to its most streamlined form for:
- Minimum redundancy
- Maximum data integrity
- Best processing performance
Normalized data occurs when attributes in the table depend only on the primary key.
5.4 Data Warehousing
Data warehouses and Data Marts: A data warehouse is a repository of historical data organized by subject to support decision makers in the organization.
Benefits of Data Warehousing
- End users can access data quickly and easily via Web browsers because they are located in one place.
- End users can conduct extensive analysis with data in ways that may not have been possible before.
- End users have a consolidated view of organizational data.
5.5 Knowledge Management
Knowledge management (KM): Knowledge management is a process that helps organizations manipulates important knowledge that is part of the organization’s memory, usually in an unstructured format.
Knowledge: Knowledge that is contextual, relevant, and actionable.
Intellectual capital (or intellectual assets): Intellectual capital is another term often used for knowledge.
*Type of knowledge:
Explicit knowledge: objective, rational, technical knowledge that has been documented. Examples: policies, procedural guides, reports, products, strategies, goals, core competencies
Tacit knowledge: cumulative store of subjective or experiential learning. Examples: experiences, insights, expertise, know-how, trade secrets, understanding, skill sets, and learning
*Knowledge Management System Cycle:
- Create knowledge
- Capture knowledge
- Refine knowledge
- Store knowledge
- Manage knowledge
- Disseminate knowledge
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