INFO MAG LESSON 1: Database Environment Database Concepts

• Data are facts, graphics, images, sound, video segment
• Information is data processed to be useful in decision making
• bit the smallest unit of data. has only 2 value ( 1 and 0 )
• byte is an 8 bits which represent one character
• field represents a combination of bytes that make up one aspect of a business object (i.e. student number, student name); also called column/attribute
• record - a collection of related data fields; also referred to as row/tuple
• file - a collection of related records; also referred to as table
• database - an organized collection of logically related data. A central repository of shared data.
• Metadata a descriptions of the properties or characteristics of the data, including data types, field sizes, allowable values, and documentation
• Database Management System is a collection of programs that enables users to create and maintain a database. It facilitates the process of defining, constructing, manipulating, and sharing database among users
• File Processing is a system used to store and manage data that involves each department or area within an organization having its own set of files, often creating data redundancy and data isolation.
• Constraint- allowable values. rule implemented to the data
• Traditional File Processing- is a file processing system stores data in separate computer files
• Disadvantage of Traditional File Processing

  • Data Redundancy- Duplicate Data
  • Limited Data Sharing- No centralized control of the data
  • Program Data Dependence- Excessive program maintenance
• Advantages of Database Approach:

  • Program Data Independence- reduce program maintenance
  • Planned Data Redundancy- leads to increased data integrity/consistency
  • Improve Data Sharing- diff users can get diff view to the data
  • Enforcement Standard- all data access is done in the same way
  • Improved Data Quality- there is a used of constraint for data validation
  • Better Data Accessibility- Use of standard data query language (SQL)
  • Increased Productivity of Application Development-Developer can focus on specific functions. Provision of high level productivity tools
• Another Advantage:

  • Improved decision support- Databases expressly designed for decision support applications
• COSTS AND RISKS OF THE DATABASE APPROACH:

  • Upfront Cost- Installation Management Cost and Complexity. Conversion Costs
  • Ongoing Costs- Requires New, Specialized Personnel. Need for Explicit Backup and Recovery
  • Organizational Conflict- Conflicts in reaching consensus on data definitions and ownership
• THE RANGE OFDATABASE APPLICATIONS:

  • Personal Database – standalone desktop database
  • Workgroup Database – local area network (<25 users)
  • Department Database – local area network (25-100 users)
  • Enterprise Database – wide-area network (hundreds or thousands of users)
• Flat files - 1960's. a database designed around a single table or file
• Hierarchical -1970's. A data model in which the data is organized into a tree-like structure; confined to up to ‘one to many relationship’
• Network – 1970's. much like the hierarchical model except that it permitted many to many relationship
• Relational (RDB)- 1980's to present. Organizes data in the form of tables/entities and establish the relationships between them by means of common fields
• Object-oriented (OODB)– 1990s - present. subscribes to a model with information represented by objects ; encapsulates both data and behavior
• Object-relational (ORD) - 1990s – present. provide a middle ground between relational databases and object oriented databases
• NoSQL – Early 2000s. new generation of databases that address the specific challenges of Big Data
• Data Warehouse - a subject oriented, integrated, time variant, non-volatile collection of data used in support of management decision making and business intelligence
• Web-enabled -data – a database with web-based interface; standard database facilities but accessed remotely
• Subject-Oriented- A data warehouse can be used to analyze a particular subject area. For example, "sales" can be a particular subject.
• Integrated- A data warehouse integrates data from multiple data sources. For example, source A and source B may have different ways of identifying a product, but in a data warehouse, there will be only a single way of identifying a product.
• Time-Variant- Historical data is kept in a data warehouse. For example, one can retrieve data from 3 months, 6 months, 12 months, or even older data from a data warehouse.
• Non-volatile- Once data is in the data warehouse, it will not change. So, historical data in a data warehouse should never be altered.