Evolution of Information Systems in the Digital World

Using productivity software and having basic knowledge of hardware, software, the Internet, and collaboration tools.

Knowing how to find, analyse, and communicate information.

To provide historical, current, and predictive views of business operations for competitive advantage.

People who grew up with constant access to digital technologies like smartphones, tablets, and computers.

How technology and the internet shape human interaction, behaviour, thinking, and communication.

A society formed through the adaptation and integration of advanced technologies into culture.

A digital platform for accessing ride-hailing services through smartphone apps.

Buying and selling goods and services over the Internet through online platforms.

An information system that manages reservations and payments online.

The use of IT to support sharing content among networks of users.

An information system that supports sharing content among networks of users.

Social media providers, users, and communities.

Technologies that simulate and reproduce human thought behaviour.

An information system that incorporates AI into its applications.

IBM Watson analysing medical data to suggest diagnoses.

AlphaGo learning from past games to improve at Go.

Tesla Autopilot using sensors to perceive the environment.

AlphaFold solving complex protein folding problems.

ChatGPT generating and understanding human-like text.

A system that stores knowledge and makes inferences.

Mechanical and computer devices performing precise, repetitive tasks.

Systems that capture, store, and manipulate visual images.

Technology that lets computers understand natural language like English.

A system that changes its behaviour based on feedback.

Currencies that exist only on the Internet and are completely intangible.

The first decentralised cryptocurrency solving the double-spend problem.

A cryptocurrency supporting smart contracts and decentralised apps.

A stablecoin pegged to the US dollar.

A digital currency used for fast international transactions.

A government-issued digital currency like China’s Digital Yuan.

El Salvador.

China (also Indonesia, Vietnam, Malaysia).

Instantaneous and low-cost payments.

They are susceptible to hacks.

A growing list of cryptographically linked records called blocks.

Raw facts.

Data that is organised and meaningful.

They face issues like redundancy, inconsistency, poor security, and lack of scalability.

A collection of organised data allowing access, retrieval, and use.

Software for creating, managing, and controlling access to databases.

Reduced data redundancy.

A database supporting one user at a time.

A database supporting multiple users simultaneously.

Database → files → records → fields → characters.

A combination of characters with a name, size, and data type.

A group of related fields.

Ensuring data is accurate, complete, and correctly formatted.

A structured collection of rows and columns storing data.

A language for retrieving and manipulating data in a database.

An interface for entering and viewing data.

A formatted presentation of extracted data.

A listing of activities that change database contents.

A tool that restores a database using logs or backups.

A tree-like data structure with records connected by links.

A model storing data in tables with rows and columns.

Managing, updating, and retrieving data.

A model using graph structures allowing many-to-many relationships.

A database storing data as objects.

A visual model showing entities, attributes, and relationships.

A database managed and accessed online via web interfaces.

Installs, configures, maintains, and secures databases.

Designs and optimises databases to meet organisational needs.

Delivery of computing services over the Internet.

Netflix, YouTube, Google Drive, Dropbox.

Healthcare, education, banking, software development.

Huge and complex datasets beyond traditional processing tools.

Volume, Variety, Velocity, Veracity, Value.

Fraud detection in finance.

Examining and interpreting data to uncover insights.

Summarising past data to identify patterns.

Analysing data to find the causes of events.

Using models to forecast future trends.

Recommending actions based on data insights.