25+ most used Tech Buzzwords – easily explained
We all hear them every day but here are some simple explanations for the most used buzzwords in tech
Every day we hear these words and sometimes they are used like everyone knows what they mean. Here you will find easy explanations for 25+ of the most used tech buzzwords.
There are thousands of meetings where people throw around tech buzzwords without ever knowing what they mean or what they stand for. I think everyone hat such a presentation where more buzzwords were displayed on the screen than you wanted to hear.
I will help you figuring out the 13 most used and most misunderstood tech buzzwords and try to explain them as easily as possible. If you need more in-depth knowledge, then I would recommend following the links I placed or looking on MoreThanDigital for more content on the topic.
When I use a word in “quotation marks”, then it means that you will find this description in this article as well.
Index
Analytics / Actionable Analytics
This term is used when they speak of analyzing “Big Data” which leads to some sort of actionable outcome. So e.g. they use customer data to find patterns and make assumptions of how to optimize the web shop for better sales and conversion.
For these analytics you usually need a big set of data that can be analyzed with tools like “Artificial Intelligence (AI)” and “Machine Learning (ML)” which you will read later.
Apps / Web-App / Native-App / Hybrid-App
One of the biggest trends in the last years is an app. Every company needs to have an app(lication) that is usually refered as a “mobile app”. A mobile app is an application that specifically runs on a mobile device while a normal application only refers to a type of software designed to provide a functionality to the user.
Web-Apps are applications that run specifically on the internet like the Facebook web-interface and native apps are applications that are specifically designed for an operating system. Best example for a native app is Skype which will be installed on the device. A Hybrid-App is the combination of an app designed for a specific operational system but the content is being fetched from a web-app (e.g. Facebook App for the smartphones)
Mobile Websites Vs. Apps – What Fits When?
Artificial Intelligence (AI)
Artificial Intelligence (AI) is a very broad term and can be used in many ways. It describes a field of study to use algorithms which learn and adapt to solve a problem. These algorithms are currently mostly trained to achieve one single goal.
Well known examples are the chess or go algorithms which outperformed their human counterpart. “Machine Learning (ML)” which will be explained later, is one kind of such an algorithm.
Leveraging Cloud & AI/ML For A Better ECommerce & Retail Experience
Artificial Intelligence Vs. Human – Are We Replaceable?
Artificial Intelligence – Marvel Of Technology Or Art?
Big Data
One of the most commonly used buzzwords because data is an important asset. This buzzword describes the very large amounts of data that companies collect/can collect to further process. It is often also referred to that the amount of data is so big that traditional tools like excel or a human can not analyze it anymore.
One of the best examples are user data e.g. Amazon is collecting. So, what kind of product you were looking for, what other products you visited, which products you bought and what intentions were measured on the website. These are million data-points per user that will be collected and used then later for analysis – See “Data Mining” for more info on this.
Blockchain
Blockchain is commonly used for the description of a distributed ledger technology. That means that records of the same information are kept on different servers in different locations to ensure better safety and prevent altering of the data.
Blockchain itself was one of the first distributed ledger technologies on the market and is a protocol to transfer data which is fully traceable, can not be altered and is stored in a decentral network of computers. Blockchain is also a synonym for the “Crypto”-currency
Blockchain – Possibilities, Applications And Use Cases For The Distributed Ledger Technology
Business Intelligence
Describes processes that are used to systematically analyze a company. Data is collected internally or externally (e.g. by ERP systems, CRM systems, Websites etc.), evaluated and presented in mostly electronic form. The goal is to gain insight into the current state of the company and to be able to make predictions for decision makings.
Chatbots
Chatbots are programs that mimic a „human like“-interactions with a human. To better interact with a person they typically use a decision-tree or are built with “Machine Learning” or Language Analysis to improve the communication and to seem more human in their way to interact.
Usually you can use Chatbots internally (internal Chats like Slack etc.) or externally (Facebook Messenger, WhatsApp, Website-Integration) to give answers, qualify leads or also other tasks, where users might prefer to chat instead of simply filling out a form.
Cloud & Cloud Computing
Often also only referred by the name “Cloud” is describing a model where you don’t have computers at home or in the company. With cloud services / “Cloud Computing” the user gets access to computing power and computing resources (like Processing Power, Disk storage etc.) via an active internet connection.
Google Drive is one of the customers facing solutions that everyone might now. This is an online drive which sits on servers around the internet. The user can simply upload the data and doesn’t have to worry about maintenance, crushes, failing hardware etc.
For businesses Amazon Web Services, Google Cloud, Microsoft Azure etc. are offering different kind of services for the business needs to outsource server capacity and maintenance work.
Crypto
Crypto is usually just used as a synonym to crypto-currencies. These currencies are created by “Blockchain” or Distributed Ledger Technology-Networks. These crypto-currencies exist originally to pay someone who offers his computing power and electricity to the network to compute the distributed ledger. But crypto could also refer to cryptography, which is the basis for the Distributed Ledger Technology-Networks, as a whole. Then it describes the process of securing the communication.
Data Mining
Is the process of examining and analyzing large amounts of data to find patterns and use these patterns to get a better insight in the collected data. Usually this involves large data-sets like you have heard before in “big data” and they use tools like “Artificial Intelligence (AI)” and “Machine Learning (ML)” to crunch the data and extract the desired patterns from the data.
DevOps (Development Operations)
It is a process in the software development that helps to streamline the Development and Operations. It tries to unify 3 departments from Development, Operations and Quality Management to create a collaboration environment where all work together and to accelerate the delivery of new features and bug-fixes.
Digital / Digitization
Digital is most commonly used to describe many fields but its original meaning is derived from digitizing analog information. This literally means taking something like a document and making a digital version of it. In business terms it is mostly referred to creating digital derivatives of documents, processes etc. With these digital versions manipulation of the file is easier and it can be automated. If the process changes as a whole, then it is referred as “Digital Transformation”.
Digitalization vs. Digital Transformation – What is the Difference?
Digital Transformation
Digital Transformation is in contrary to “Digitization” the rethinking of business models, culture, processes, structures etc. due to new technological advanced. A new technology might become available and this is the reason to think about new business models and change the processes in the company. Digital Transformation is also changing basic assumptions and ways a company used to work.
Corporate culture as the most important factor in digital transformation
What is “Digital Transformation”? – Definition and explanation
5 Trends as drivers for the digital transformation of all industries
95% Transformation and only 5% Digital – True Digital Transformation
Disruptive
Especially in the start-up world you are going to hear this term often. It is referred to a a new technology, business model or something else that can be so successful that existing products, companies and services might be obsolete and it changes the whole market.
9 Disruptive Business Models For 2020 – New Opportunities For Companies
Ecosystem
In economy an ecosystem is a system of organizations and individuals who are being directed by an ecosystem orchestrator to create value with a common value proposition. This way a customer sees only one common goal of all individual companies and individuals involved.
Best known digital ecosystem is maybe Amazon which offers an ecommerce platform, payment services, movie/music services, logistics services etc. and is the ecosystem orchestrator for many businesses and 3rd-parties involved.
What Is A Digital Ecosystem? – Understanding The Most Profitable Business Model
Front-End / Back-End
Front end describes all the parts of a website, application or service where the user can interact with. When you are surfing on a Website, you usually only see the “Front End” of the website. There you can only interact in a limited way with the code itself.
The service itself is running in the “Back End”, this describes the part of websites, “App” etc. that is typically not visible to users and includes the application itself, web servers, databases, code and much more.
Industry 4.0
The term describes Smart Factories where IoT and other technologies are used to analyze the work, make improvements and use the generated data to automate the maintenance, predict problems or also share data with other parties involved in the production. This interaction helps to improve the production as well as the communication within the factory. Technologies like “Machine Learning” are used as well as “Big Data” to improve the decision-making processes and insights.
Internet of Things (IoT)
Internet of Things (IoT) describes the possibility to add sensors, controls and internet access to different things. This can include cars, coffee-machines, industrial robots etc. which can all be connected, analyzed and maybe controlled over the internet. A typical example found at home is the lighting that can be controlled with Alexa, Google or Siri. The light bulb has a chip which connects the bulb to the internet and over a platform Alexa etc. can control this light bulb at home.
IoT Solutions – structure and processes explained
IoT Toolkit – The 3 Building Blocks Of Every IoT Solution
Machine Learning (ML)
Machine Learning is an example of a technology used within the field of “Artificial Intelligence (AI)”. It gives computers the ability to learn with new data and to adapt without specifically programming the algorithm new. This type of algorithm is used to make predictions about user behavior or also selects and personalizes content.
E.g. Facebook uses Machine Learning to personalize the content on everyone’s news feed so they stay the longest on the platform. The algorithm learns what catches your attention and optimizes the content for your liking.
Machine Learning – Basics And Definition Explained For Beginners And Managers
Microservices / Microservice Architecture
This is a way of programming very complex applications and software by splitting them up into small manageable services. The individual “Microservices” then get connected via a programming interface that uses a neutral programming language. This way the software is modular and can be developed, scaled, be replaced as single parts instead of changing the whole complex system.
Net Neutrality
This buzzword popped up due to the latest development. Net Neutrality basically means that every service on the internet has the same kind of speed, bandwidth-allocation and access – no matter where the request comes from. This concept is currently being challenged where it could be possible that only company paying extra to the Internet Service Providers (ISP) could get the fast lanes. E.g. Netflix needs to pay in every country the ISP to give people access to Netflix as a video service.
Platform
Platforms are one of the most “Disruptive” Business Models at the time. Most new Fortune 500 companies are in some kind involved in a platform business model. The basic model is always the same. A large variety of suppliers (content, products, services etc.) are using one platform in the middle to offer the goods. On the other side is the demand where a large number of buyers get attracted to the platform because they can find many suppliers at one place. So the platform brings together many suppliers and many customers.
There are various business models possible from membership models to commission basis or advertisement to generate revenue as a platform.
Platforms And Content – The Business Model Of The 21th Century
Quantum Computing
Currently the technologies of the silicon chips (CPU, GPU etc.) are hitting the physical boundaries as they can not get any smaller or much faster. This is why quantum computing is in the news for quite some time. Big companies like Google, IBM etc. are exploring ways how to use quantum mechanics to process data and to compute software. In contrary to ordinary chips these quantum computers can not only process 0 and 1, they can literally compute infinite number of states at once, which would make them very powerful in computing large quantities of data. The technology is still in experimental phase and we will not see anytime soon a commercial application widely available.
User Interface (UI) & User Experience (UX)
Both are often used as synonym even tough they have very different meanings. The User Interface (UI) explains the parts of an application, website, computer etc. which the user can manipulate. So everything from the website-menu to buttons and even keyboards or touchscreen can be part of the User Interface (UI). The User Experience (UX) is how the user feels, the emotions he gets and the ease-of-use he has when interacting with a product or service. This can be also the communication with the customer and the product or the design of a service.
Virtual Reality and Augmented Reality (VR & AR)
Virtual Reality is a term that describes a computer-generated reality, like a video game, in which a user can interact. Often, we see special gear like special glasses, gloves etc. that are used so you can interact in the virtual world while seeing what you are doing.
Augmented Reality is on the contrary a virtual overlay of the actual world with sound, videos or other computer-generated elements. We sometimes see this in Science-Fiction movies where someone has glasses on and they see the details of the person they are speaking with or some information on the street. Augmented Reality is used e.g. in cars to display the navigation arrows directly on the front window of the car so it looks like the arrows are on the street.
Voice Recognition & Natural Language Processing (NLP)
Voice Recognition is a part of computer science where computers turn the spoken word of a human into text. A simple example of Voice Recognition are services like Alexa, Google Assistant, Siri etc. which can be used to dictate texts or to transcribe videos.
Natural-Language-Processing on the other hand is focusing on the interaction between computers and the human language. NLP tries to improve 3 different factors: speech (voice) recognition, natural language understanding and natural-language generation. These fields then include the uptake of what you say, the understanding what you say and then also the natural sounding reaction to what you say.
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