An automation glossary
Automation software is expanding its reach: both in terms of functionality and foothold. The more useful it grows, however, the more terminology there is to go along with it. After a while, it can be hard to keep track of the meanings behind the terms.
So, here’s a handy automation glossary. Let’s demystify the terminology that surrounds business process automation software.
AI – artificial intelligence
Artificial intelligence (AI) is the ability of a computer to simulate human thinking and understanding. It’s often talked about alongside automation, but the two are not the same thing. AI can analyse and learn. Automation, in contrast, simply does as it is told.
Algorithms are a core part of computing, and so earn a place in the automation glossary. An algorithm is a step-by-step guide outlining how to do something. In automation software, algorithms are the precise instructions telling the computer how to do a task or manipulate data.
It wouldn’t be much on an automation glossary without explaining the term ‘automation’. Automation refers to making a task, workflow or process happen automatically. So, routine tasks are completed in an efficient way, without human intervention.
Automation anxiety is the name given to the fearmongering and worry that the introduction of automation can generate. Most commonly, this relates to the fear of job loss or replacement by automation software.
Automation disruption refers to the major change and upheaval the automation has, and is, causing. These changes pertain to the traditional workplace, the job market and the daily tasks we complete.
BPA – business process automation
A major entry in this automation glossary, business process automation is the full name for automation software in businesses. It refers to the automation of businesses processes, whether those are simple tasks or complex workflows.
CRM – customer relationship management
Customer relationship management is a strategy for managing and monitoring all the interactions a business has with each customer. It allows companies to provide a more efficient, personalised service to their customers.
DBA – database administrator
Database administrators are the overseers of a business’s computer systems. So, they manage the creation, maintenance and security of your databases. They often work closely with automation software, managing the rules it follows and access it has to your databases.
If statements are part of programming. They’re statements that set out a condition, and tell a computer what to do if that condition is (or isn’t) met. They’re in this automation glossary because they relate to how you tell your automation solution what to do and when.
Integration relates to the ability of the automation software to communicate and work with other programs and technology. It’s most often referred to as system integration.
ML – Machine learning
Machine learning is a subsection of AI that focuses on allowing machines to learn new skills. So, over time, a computer becomes able to solve new problems and gets better at completing given tasks. This can then be used to make automated decisions, hence ML’s inclusion in the automation glossary.
NLP – Natural language processing
Natural language processing is another branch of artificial intelligence. The goal of NLP is to make computers better at understanding people as they speak naturally. So, you can talk to the computer as you would another human being, and NLP would enable it to understand you.
Parsing is where your automation looks for and extracts information from inbound text. For example, emails, documents, messages and so on. As a handy feature of automation, parsing comes in many forms. You’ll have email parsing, document parsing, language parsing, etcetera.
RPA – robotic process processing
Robotic process automation is another big hitter in any automation glossary. Generally speaking, RPA is a fancy name for god old business process automation. It invokes the idea of a robot workforce that you pass your tasks onto as a way to describe what automation does.
Rule-based logic exists at the core of most automated processes. That is, automation operates on a rule-based system. A rule-based system is one that applies human-made rules to run the desired action.
Sentiment analysis is a language parsing tool that analyses written text to find the sentiment (or feeling) behind it. With automation, this is a process that can happen automatically for any inbound written text. For example, emails, blogs, social media posts, live chat conversations, and online reviews.
Often talked about when discussing RPA, software bots are another commonly misunderstood term in the automation glossary. Simply put, they’re programs designed to automate a task. Software bots don’t have a physical presence, instead existing behind our screens. They can take several forms. For example, a chatbot, web crawler bots and rule-based automation bots.
A trigger is a business event that sets off an automated workflow. For example, an email hits your inbox, and that sets off your email parser, which finds a triggering keyword which sets off the next task, and so on.
Finally, the last entry in the automation glossary is workflows. Workflows are a series of tasks or processes that take a given job from start to completion. Automation software can handle some of these tasks, or entire workflows.
From automation glossary to free trial
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