Information vs Material Goods

Information behaves differently from physical objects. It is specified by data and can be transmitted, stored, categorized, searched, or converted into other representations without degrading. You can freely combine and manipulate information in ways impossible with material goods, and it operates independently of any fixed medium or location. Unlike physical inventory, information can also be unclear, vague, or imprecise — ambiguity is part of its nature.

Information as Production Factor

When an organization treats information as a production factor, it must invest in data gathering, storage, and processing infrastructure. The underlying data must be complete, available, and correct to support reliable decision-making. An information system allows users to store and connect information interactively — asking questions and receiving answers — with the World Wide Web being the most familiar example.

Database Management Systems

Database management systems are application-independent platforms for storing and querying data. Every DBMS has a management component and a storage component; the most common flavor today is SQL-based. These systems let multiple applications share the same data without each one reinventing how to organize, protect, or retrieve it.

The Relational Model

A relational database structures data using tables with rows and columns, and handles relationships through keys. Attributes are the column headings — the topics you want to track. Domains define the allowed values for each attribute. Primary keys are unique identifiers for each row in a table, ensuring no two objects are confused.

Consider a STUDENT table with attributes StudentID, Name, Age, and Major. The domains might specify that StudentID accepts only numbers, Age ranges from sixteen to one hundred, and Major allows only "CS" or "Math." StudentID serves as the primary key because each student gets a unique identifier.

Properties of Keys

Good keys are unique (no duplicates), minimal (no unnecessary columns), application-independent (not tied to one specific program), and without semantics — meaning the key itself carries no business meaning, just an identifier. This keeps the system flexible when business rules change.

Relational DBMS in Practice

Relational database management systems store all data in tables and describe those tables — their attributes, keys, and integrity rules — in a schema. SQL serves as the descriptive language for defining, querying, and modifying data. By separating physical storage from applications, RDBMSs achieve data independence: changes in how data is physically stored usually require no changes in the programs that use it.

RDBMSs support many concurrent users while preventing transactions from corrupting each other's work. They enforce consistency and integrity rules, protect against data loss, and guard against unauthorized access through permissions and authentication.

Big Data

Big Data refers to data sets so large, fast-moving, and diverse that traditional software cannot store, process, or analyze them effectively. These sets often include unstructured or semi-structured data from social media, sensors, logs, transactions, and multimedia.

The three classic characteristics are volume (terabytes to zettabytes), variety (many formats and types), and velocity (continuous streams that need real-time or near-real-time processing). Two more V's are frequently added: value, because the goal is turning all this data into business or societal benefit that justifies the investment, and veracity, because data quality is uneven and much of it may be inaccurate or incomplete.