Glossary of Technology Terms

Field of computer science that develops machines and systems capable of performing tasks that normally require human intelligence. AI includes machine learning, natural language processing and computer vision, transforming industries through intelligent automation.

Set of protocols and tools that allows different applications to communicate with each other. APIs are fundamental for systems integration, allowing developers to build applications that interact securely and efficiently with other services.

Process of examining data to discover patterns, trends and actionable insights. Analytics transforms data into informed decisions, enabling process optimisation, understanding customer behaviour and predicting future outcomes.

Process of verifying user identity before granting access to systems or resources. Modern methods include passwords, multi-factor authentication and biometrics, which are critical for maintaining security and protecting confidential information.

Specialised database that stores and searches embeddings (numerical vectors). Vector databases are essential for RAG systems, enabling fast semantic search and precise retrieval of relevant information.

Enormous volumes of structured and unstructured data generated by companies daily. Big Data offers valuable insights when analysed correctly, enabling data-driven decisions and improving competitiveness.

Distributed ledger technology that stores data in an immutable and decentralised way. In traceability, blockchain guarantees the authenticity and integrity of records, enabling complete audits and creating trust across the entire supply chain.

Business management discipline that focuses on optimising business processes. BPM combines analysis, design, execution and monitoring of processes to improve efficiency, reduce costs and increase customer satisfaction.

Set of tools and processes that collect business data and convert it into actionable information. BI enables visualisation of key metrics, identifying opportunities and facilitates strategic decision-making based on data.

Practices that automate code integration, testing and application deployment. CI/CD enables frequent and reliable releases, reducing time to market and improving quality through continuous feedback.

Model for delivering computing services (servers, storage, software) via the internet rather than local infrastructure. Cloud provides flexibility, scalability, cost reduction and access from anywhere, being fundamental for digital transformation.

Software units that package code, dependencies and configuration needed to run an application. Containers (like Docker) ensure applications run consistently in any environment, simplifying deployment and scaling.

Complete network of activities, from obtaining raw materials to delivering the final product to the customer. An efficient supply chain optimises costs, reduces delivery times and improves customer satisfaction through complete visibility at every stage.

Visual interface presenting real-time metrics, KPIs and data. Dashboards enable rapid performance monitoring, instant problem identification and facilitate communication of results to stakeholders.

Branch of Machine Learning that uses deep neural networks (multiple layers) to process information. Deep Learning is especially effective for image recognition, natural language processing and complex tasks requiring hierarchical learning.

Philosophy and set of practices that integrates software development with IT operations. DevOps automates deployments, improves team collaboration, accelerates software delivery and increases reliability through continuous integration and testing.

Platform for creating, distributing and running applications in containers. Docker simplifies deployment, ensures consistency between environments and facilitates collaborative work between developers.

Numerical representation of words, phrases or documents in vector space. Embeddings capture semantic meaning, enabling AI systems to understand similarity between texts and perform efficient semantic search.

Process of converting readable information into unreadable code using mathematical algorithms. Encryption protects sensitive data during transmission and storage, ensuring only authorised users can access it.

Fundamental process in data integration that extracts information from source systems, transforms it into a standard format and loads it into a target system. ETL is essential for data migration, system synchronisation and consolidated data analysis.

Family of language models that generate coherent and contextual text. GPT has revolutionised AI applications through its ability to understand complex context and generate natural, useful responses.

Cloud model that provides computing infrastructure (servers, storage, networks) on demand. With IaaS, companies access scalable resources without investing in physical hardware, paying only for what they use.

Process of connecting different software systems so they function as a cohesive unit. Integration allows independent applications to share data and processes, eliminating information silos and improving business collaboration.

Network of physical devices equipped with sensors and connected to the internet to collect and share real-time data. In industrial contexts, IoT enables remote process monitoring, predictive maintenance and intelligent operations automation.

Lightweight format for storing and exchanging data in text. JSON is widely used in APIs and web applications for its simplicity, readability and compatibility with multiple programming languages.

Quantifiable indicator that measures performance of crucial business aspects. KPIs enable progress monitoring towards objectives, identifying areas for improvement and communicating results clearly throughout the organisation.

Open-source platform for orchestrating and managing containers at scale. Kubernetes automates deployment, scaling and operation of containerised applications, facilitating complex infrastructure management.

AI models trained on enormous quantities of text to understand and generate natural language. LLMs like GPT-4 can answer questions, draft content, translate languages and assist with multiple tasks, revolutionising human-machine interaction.

Set of products manufactured under the same conditions and during the same period. Batch identification is crucial for traceability, quality control and recall management, enabling rapid withdrawal of defective products from the market.

AI subset where systems learn from data without being explicitly programmed. Machine learning models improve with experience, identifying patterns in data to make increasingly accurate predictions or decisions.

Software architecture that divides applications into small independent services, each with its own database and logic. Microservices improve scalability, flexibility and allow teams to develop components autonomously and deploy updates rapidly.

Security method requiring multiple forms of verification (password, temporary code, biometric data) to gain access. MFA significantly increases account security against unauthorised access.

AI field focused on enabling machines to understand, interpret and generate human language. NLP enables applications such as chatbots, sentiment analysis, automatic translation and information extraction from text.

Art of formulating precise instructions to obtain better responses from AI models. Prompt Engineering improves output quality through writing, context and structure techniques, being crucial for maximising the value of AI systems.

Technique combining language models with retrieval of relevant information. RAG allows AI systems to generate accurate responses based on up-to-date documents, reducing hallucinations and providing verifiable, contextual information.

Architectural style for designing web APIs using standard HTTP protocols. REST is simple, scalable and widely adopted, allowing applications to communicate efficiently over the internet.

Technology using software robots to automate repetitive business processes. Robots can perform tasks such as data entry, document processing and transaction management without human intervention, improving operational efficiency and reducing errors.

Software delivery model where applications are hosted in the cloud and accessed through a web browser. SaaS eliminates the need for local installation, offers automatic updates and reduces operational costs.

Practice of managing the entire supply network, including procurement, processing and delivery. SCM focuses on optimising costs, improving efficiency and increasing visibility for data-driven decisions.

Practice of protecting systems, networks and data against unauthorised access, theft and damage. IT security is fundamental for any digital transformation, requiring multi-layer protections and constant updating against new threats.

Device that detects changes in the physical environment (temperature, pressure, light, movement, etc.) and converts them into measurable signals. Sensors are essential components of IoT and industrial automation systems.

Process of modernising business operations through the adoption of digital technologies. Digital transformation redefines processes, improves customer experience and creates new business opportunities, being imperative in today's economy.

Revolutionary neural network architecture using an attention mechanism to process data sequences. Transformers are the foundation of modern language models like GPT, enabling efficient and parallelisable information processing.

Ability to record and track the movement of a product throughout its entire supply chain, from raw material to final delivery. Traceability provides complete transparency, improves quality control and enables rapid identification of problems or defective batches.

Ordered sequence of tasks and processes within an automation system. A workflow defines how data and documents move from one stage to another, ensuring each process is executed in the correct order and by the right people.