Top 10 Technology Buzzwords in 2019

Top 10 Technology Buzzwords in 2018
Top 10 Technology Buzzwords in 2019

Top 10 Technology Buzzwords in 2019

Nowadays, whenever there is technology news in media, we listen to the new Top 10 Technology Buzzwords in 2018. Today we are going to understand the most popular technology buzzwords/terms that we all should at least have the basic idea.


 “Whether you are a doctor, engineer, developer, marketer or even in sales, it is always good to have a basic understanding of what is going on in latest trends and how information technology is contributing to our day-to-day life!” 


If you are in any type of a technical profession, I am sure someone at some point has asked you this question.

List of  trending  Technology Buzzwords:

1. Big Data

Big Data is the most common technology buzzword we hear these days which is used to describe very huge amounts of data collected by companies or institutions.

Big Data is a large set of data and information that computers can analyze and compute for a specific domain.

Today’s computers produce the data in an easy-to-understand packet for you to make decisions.

Examples include:
1. The New York Stock Exchange generates about one terabyte of new trade data per day.

2. Social Media – Statistic shows that 500+terabytes of new data gets ingested into the databases of social media site Facebook, every day. This data is mainly generated in terms of photo and video uploads, message exchanges, putting comments etc.

3. A single Jet engine can generate 10+terabytes of data in 30 minutes of flight time. With many thousand flights per day, generation of data reaches up to many Petabytes.

2. BlockChain

Over the course of a one-year period, Google search requests for the keyword “blockchain” have increased by 250%.

In simple terms, a blockchain can be described as an encrypted append-only transaction ledger.

A blockchain, originally blockchain technology buzzword is a growing list of records, called blocks, which are linked using cryptography. Each block contains a cryptographic hash of the previous block, a timestamp, and transaction data.

A new type of database, blockchain allows users to see a history of all transactions that have occurred on a record, including verification and validation.

This is a change from the traditional databases, which overwrites a record when there is a change. With the growth of cryptocurrencies such as bitcoin, blockchain technology is being used to record financial transactions, and due to its secure nature, it is also being considered to record medical changes.

3. Chatbots

Chatbots were first started with Microsoft Word’s famous paperclip helper, and now numerous instant messaging programs.

Nowadays, most of the company websites have implemented online Chatbots to offer digital chatbots that can offer customers help and support.  Slack is one example of this, while other companies have pop-up windows within a webpage to offer support for customers.

Machine learning and language analytics can help enable the chatbots to seem more human in their interactions with consumers.

4. Machine Learning (ML)

“Machine Learning is the science of getting computers to learn and act like humans do, and improve their learning over time in an autonomous fashion, by feeding them data and information in the form of observations and real-world interactions.”

Machine Learning (ML) is the field of study that gives computers the ability to learn without being explicitly programmed.

It is an application of artificial intelligence (AI) that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed.  Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.

5. Artificial Intelligence (AI)

Artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals.

In computer science, AI research is defined as the study of “intelligent agents“: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.

Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem-solving”.

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. Some of the activities computers with artificial intelligence are designed for include:

  •  Speech recognition
  •  Learning
  •  Planning
  •  Problem-solving

6. Dark Data

According to Gartner, dark data is “the information assets organizations collect, process and store during regular business activities, but generally, fail to use for other purposes”.

Dark data is data which is acquired through various computer network operations but not used in any manner to derive insights or for decision making.

In an industrial context, dark data can include information gathered by sensors and telematics.

7. Microservices

A microservice is a software development technology buzzword, and technique—a variant of the service-oriented architecture (SOA) architectural style that structures an application as a collection of loosely coupled services.

In a Microservices architecture, services are fine-grained and the protocols are lightweight. The benefit of decomposing an application into different smaller services is that it improves modularity and makes the application easier to understand, develop, and test and more resilient to architecture erosion.

It parallelizes development by enabling small autonomous teams to develop, deploy and scale their respective services independently. It also allows the architecture of an individual service to emerge through continuous refactoring.

Microservices-based architectures enable continuous delivery and deployment.

Computer microservices can be implemented in different programming languages and might use different infrastructures.

8. Quantum Computing

Quantum computers could one day provide breakthroughs in many disciplines, including materials and drug discovery, the optimization of complex systems, and artificial intelligence. But to realize those breakthroughs, and to make quantum computers widely usable and accessible, we need to reimagine information processing and the machines that do it.

Quantum computing is computing using quantum mechanical phenomena, such as superposition and entanglement.

A quantum computer is a device that performs quantum computing. Such a computer is different from binary digital electronic computers based on transistors.

Whereas common digital computing requires that the data be encoded into binary digits (bits), each of which is always in one of two definite states (0 or 1), quantum computation uses quantum bits or qubits, which can be in superpositions of states.

9. Data Mining

Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.

Data mining is the task of sorting large data sets to identify patterns and establish relationships to solve problems through data analysis.

10. Internet Of Things (IOT)

The Internet of Things (IoT) is the network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors and connectivity which enables these things to connect and exchange data.

These devices can be cars, home automation systems or your everyday toaster.



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