Robotic Process Automation dictionary

# Autonomous Enterprise

Robotic Process Automation dictionary

16.12.2024

Automation in modern business is on everyone’s lips. Company management boards monitor the implementation of KPIs related to the automation of the work environment; shareholders count the profits and savings achieved thanks to robotization, and subsequent generations of IT adepts learn concepts related to automation because this field has a bright future.

Basic concepts

The adventure with automation, like everything else, is worth starting from scratch. These constitute three concepts:

Robotic Process Automation (RPA): Technology that uses software robots (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 and artificial intelligence (AI) technologies like machine learning and natural language processing to automate more complex tasks and make decisions based on data insights.
Hiperautomation: A strategic approach combining multiple technologies such as RPA, AI, and machine learning to achieve end-to-end automation of business processes.
Autonomous Enterprise: An organization that leverages advanced AI, automation, and data analytics to operate efficiently with minimal human intervention.

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

Artificial Intelligence (AI): The simulation of human intelligence in machines, enabling them to perform tasks like decision-making, learning, and problem-solving.
Machine Learning (ML): A subset of AI that involves the use of algorithms and statistical models to enable systems to learn from data and improve their performance over time without being explicitly programmed.
Natural Language Processing (NLP): A field of AI focused on 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 vast datasets to understand and generate human-like text and respond intelligently to various inputs. Examples are generative AIs as ChatGPT, Dall-E and Llama.
Neural Network (NN): A type of AI model inspired by the human brain’s structure, consisting of interconnected layers (neurons) that process information and learn patterns in data.

Automation is often considered synonymous with robotization. They are not identical (although very similar), but this does not change the fact that robots are used in both cases. What are robots? We hasten to answer:

Robot: A software program or bot that performs automated tasks, either attended (with human supervision) or unattended:
- Attended Robot: A robot that works alongside human users, requiring interaction or supervision to perform tasks.
- Unattended Robot: A robot that operates independently, executing tasks without human intervention.

Automation processes

Automation covers many processes, which include:

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 that define 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 within automation workflows to manage resources like credentials, connection strings, or configuration values.
Queues: A feature used to manage and prioritize work items for robots, ensuring tasks are processed efficiently and in the correct order.

Work on automation

It is worth discussing the automation work process itself separately, because it is complex, and when ordering automation for his company, the client will have to take into account that the supplier may use the following terms in communication. They are sorted alphabetically because each one is equally important:

Studio: A development environment used to create and design automation workflows and scripts for RPA processes.
Action Center: A feature or platform where human users can intervene in or approve automated processes, typically to handle exceptions or special cases.
AI Unity: Tokens used when using AI in UiPath.
Automation Hub: A centralized platform where automation ideas are collected, prioritized, and implemented within an organization.
CI/CD continuous integration/continuous delivery: A software development approach that involves automatically testing and integrating code changes frequently (CI) and deploying updates regularly and reliably (CD).
Change Request (CR): A formal proposal to modify a system, process, or product due to new requirements or issues discovered during implementation.
Database (DB): A structured collection of data that is stored electronically and managed to enable efficient data retrieval and manipulation.
Full Time Equivalent (FTE): A unit that measures an employee’s involvement in a project or task based on full-time working hours (e.g., 1 FTE equals one person working full-time).
Orchestrator: A central management tool used to schedule, monitor, and coordinate multiple robots or automation processes.
Proof of Concept (PoC): A small-scale demonstration or project to verify the feasibility or potential success of a concept or idea.
Subject Matter Expert (SME): A person with deep expertise and knowledge in a specific area or domain.
User Acceptance Tests (UAT): A testing phase where end-users validate that a system or application meets business requirements and functions correctly before its final release.
UiPath Academy: An online learning platform providing training and certifications on UiPath tools, RPA, and automation best practices.

It is worth mentioning separately three types of documentation used in work on automation:

Process Description Documentation/Process Detailed Documentation (PDD): Documentation that outlines the steps, activities, and responsibilities involved in a specific business process.
Solution Description Documentation (SDD): A document that describes the overall solution architecture, features, and implementation plan for a project.
Technical Description Documentation: A detailed document that provides technical specifications and guidelines for building or deploying a system or solution.

It is also worth distinguishing two types of data mining:

Communications Mining: The process of extracting valuable insights from communications data, such as emails or chat logs, using AI techniques like NLP.
Process Mining: A technique that analyzes event logs from information systems to understand, monitor, and improve business processes.

Tools

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

Document Management System (DMS): Software that helps manage, store, and track electronic documents and digital versions of paper documents.
Document Understanding: A technology 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 like finance, HR, procurement, and inventory management into a unified system.
Optical Character Recognition (OCR): A technology used to convert different types of documents (e.g., scanned paper documents, PDFs) into editable and searchable digital data.
Intelligent OCR: An advanced form of OCR that not only recognizes text but also understands context and extracts meaningful information from documents.

ANY QUESTIONS?

LET'S TALK!

Leave your phone number.
We will answer all your questions!

/ We know how