RPA Glossary: Key Concepts in Process Automation

Instead of just nodding along in IT meetings, take the initiative and start confidently using the terminology that drives modern operational efficiency. Effective business process automation requires a precise distinction between Robotic Process Automation (RPA) and comprehensive hyperautomation to accurately match solutions to a company’s real needs. This guide demystifies technical jargon, explaining key concepts from PDD documentation to UAT testing, which will allow you to confidently plan implementations and effectively manage digital transformation. This is essential knowledge for any manager or specialist who wants to have a real impact on their organization’s development.

Basic concepts

Like everything else, it is worth starting your automation journey with the basics. These consist of three concepts:

• Robotic Process Automation (RPA) – a technology that uses software (bots) to automate repetitive, rule-based tasks typically performed by humans, such as data entry or form processing. Examples of tools in this area include UiPath, BluePrism, and PowerAutomate.
• Intelligent Process Automation (IPA) – a combination of RPA with artificial intelligence (AI) technologies, such as machine learning and natural language processing, to automate more complex tasks and make decisions based on data analysis.
• Hyperautomation – a strategic approach combining various technologies, such as RPA, AI, and machine learning, to achieve full end-to-end business process automation.

Since artificial intelligence has entered the scene and is one of the foundations of modern automation, it is worth introducing concepts related to it:

• Artificial Intelligence (AI) – the simulation of human intelligence in machines, enabling them to perform tasks such as decision-making, learning, and problem-solving.
• Machine Learning (ML) – a subset of artificial intelligence that involves the use of algorithms and statistical models to enable systems to learn from data and improve their performance without explicit programming.
• Natural Language Processing (NLP) – a field of artificial intelligence aimed at enabling machines to understand, interpret, and respond to human language in a meaningful way.
• Large Language Models (LLM) – advanced NLP models, such as GPT or BERT, trained on massive datasets that understand and generate human-like text and intelligently respond to various queries. Examples include generative AI models for working with natural language, such as ChatGPT, Dall-E, or Llama.
• Neural Network (NN) – a type of AI model inspired by the structure of the human brain, consisting of connected layers (neurons) that process information and learn patterns in data.

Automation is often treated as synonymous with robotization. They are not identical (though very similar), but that does not change the fact that both use robots. What are robots? We provide the answer:

• Robot – a computer program or bot that performs automated tasks, both attended and unattended:
  • Attended Robot – a robot that works alongside users, requiring interaction or supervision to perform tasks.
  • Unattended Robot – a robot that operates independently, performing tasks without human intervention.

Automation processes

Automation includes many processes, which include, among others:

• Activities – actions or tasks defined within an automation workflow, such as data extraction, validation, or sending notifications.
• Workflows – a series of connected steps or actions defining an automated business process from start to finish.
• Selectors – elements used in RPA to identify and interact with specific user interface elements, such as buttons or text fields.
• Assets – configurable variables or settings used in automation workflows to manage resources, such as credentials, connection strings, or configuration values.
• Queues – a feature used to manage and prioritize work items for robots, ensuring tasks are processed in the correct order.

Working on automation

It is worth discussing the process of working on automation separately, as it is complex, and a client ordering automation for their company will have to account for the fact that the provider may use the following terms in communication; they are sorted alphabetically, as each is equally important:

• Studio – a development environment used to create and design workflows and scripts for RPA processes.
• Action Center – a feature or platform where users can intervene or approve automated processes, typically to handle exceptions or special cases.
• Autonomous Enterprise – an organization that uses advanced artificial intelligence, automation, and data analytics to operate efficiently with minimal human supervision.
• AI Unity – tokens used when utilizing AI in UiPath.
• Automation Hub – a central platform where automation ideas are collected, prioritized, and implemented within an organization.
• CI/CD continuous integration/continuous delivery – the process of continuous integration (CI) of code changes, automated testing, and continuous delivery or deployment (CD). It is a set of practices and tools that allow for fast, automated, and reliable delivery.
• Change Request (CR) – a formal proposal to modify a system, process, or product due to new requirements or issues identified during implementation.
• Database (DB) – a structured collection of data that is stored electronically and managed to ensure efficient retrieval and manipulation of data.
• Full Time Equivalent (FTE) – a unit measuring an employee’s commitment to a project or task based on full-time working hours (e.g., 1 FTE is one person working full-time).
• Orchestrator – a central management tool used for scheduling, monitoring, and coordinating the work of multiple robots or automation processes.
• Proof of Concept (PoC) – a demonstration or small-scale project aimed at confirming the feasibility or potential success of a concept or idea.
• Subject Matter Expert (SME) – a person with in-depth knowledge and expertise in a specific area or field.
• User Acceptance Tests (UAT) – a testing phase where end-users verify that the system or application meets business requirements and functions correctly before final deployment.
• UiPath Academy – an online educational platform offering training and certifications regarding UiPath tools, RPA, and automation best practices.

It is worth pointing out three types of documentation used in automation work:

• Process Description Documentation/Process Detailed Documentation (PDD) – documentation describing the steps, actions, and responsibilities associated with a specific business process.
• Solution Description Documentation (SDD) – a document describing the general architecture of the solution, its functions, and the project implementation plan.
• Technical Description Documentation – a detailed document containing technical specifications and guidelines for building or implementing a system or solution.

It is also worth distinguishing two types of data mining:

• Communications Mining – the process of extracting valuable information from communication data, such as emails or chat logs, using AI techniques such as NLP.
• Process Mining – a technique that analyzes event logs from IT systems to understand, monitor, and improve business processes.

Tools

Automation itself is one of the tools for improving a company’s operational efficiency, but it must be emphasized that it consists of many tools – the most important of which include:

• Document Management System (DMS) – software enabling the management, storage, and tracking of electronic documents and digital versions of paper documents.
• Document Understanding – a technological solution that combines OCR, NLP, and AI to extract, classify, and process data from documents.
• Enterprise Resource Planning (ERP) – software that integrates various business processes, such as finance, HR, procurement, and inventory management, into a unified system.
• Optical Character Recognition (OCR) – technology used to convert various types of documents (e.g., scanned paper documents, PDF files) into editable and searchable digital data.
• Intelligent OCR – an advanced form of OCR that not only recognizes text but also understands context and extracts relevant information from documents.