Top 10+ Technology Trends in 2019 you must know.

Technology is increasing day by day in such a way that you will want to know which technology is good that you have learned well and earn money. Keeping these things in mind, we will push this post forward and know which technology is there. Which will make you a better and successful person in 2019

What is Technology

Technology is the use of scientific knowledge for practical purposes or applications, whether in the industry or in our everyday life. Therefore, basically, whenever we use our scientific knowledge to achieve some specific purpose, then we are using technology. By the way, it is slightly more than that. Technology usually involves a specific piece of equipment, but this device can be incredibly simple or shiny. This can be the way to search the wheel, computer and MP3 players all the way.

In another words –

Technology is a knowledge devoted to the creation of equipment, processing processes and materials. The term “technology” is broad, and everyone has its own way of understanding its meaning. We use technology to accomplish various tasks in our daily lives; in a nutshell; We can describe technology as products and processes that are used to simplify our daily lives. We use technology to expand our abilities, so that people become the most important part of any technical system.

Technology is also an application of science that is used to solve problems. But it is important to know that technology and science are separate topics that work by hand to meet specific tasks or to solve problems.

Top 10+ Technology trends and everything you need to know.

1 Artificial Intelligence (AI)

According to John McCarthy’s father of Artificial Intelligence, it is “science and engineering to create intelligent machines, especially intelligent computer programs”.

Artificial Intelligence is a way to make a computer, a computer-controlled robot or a software that wisely thinks, wisely thinks in the same way.

AI is studied with how the human brain thinks, and how humans learn, decide and work while trying to solve any problem, and then on the basis of developing intelligent software and systems Use the results of this study.

Example of Artificial Intelligence (AI)

Smart Cars and Drones

Music and Media Streaming Services

Video Games

Online Ads Network

Navigation and Travel

Smart Home Devices

Smartphones

2. Machine Learning

Machine Learning (ML) equips computers to learn and interpret so that it can be programmed to do so clearly. Here, as a “computer”, also known as “model”, is in contact with the set of new data, they customize independently and to explain the available data and to identify the hidden pattern To learn from earlier calculations. This includes data analysis and automation of analytical model-making using several ML algorithms. ML enables computers and computing machines to detect and identify hidden insights, when exposed to new data sets, without programming to look where.

Application of Machine Learning

Virtual Personal Assistants

Predictions while Commuting

Videos Surveillance

Social Media Services

Email Spam and Malware Filtering

Online Customer Support

Search Engine Result Refining

Product Recommendations

Online Fraud Detection

Financial Services

Marketing and Sales

Healthcare

Government

Transportation

3. BlockChain

A blockchain is a long series of data entries. There is no rocket science involved here. The catch here is that there is no person or organization in charge of Blockchain for that matter. Each record is known as a block. When a person joins a block, every person who has ever added a block on the chain is informed. This makes the whole process very transparent and does not involve any arbitrator.

Blockchain is a digital, distributed, and decentralized bookkeeping that is built into the most virtual currencies that are responsible for logging all transactions without the need of a financial intermediary, such as the bank. In other words, this is a new tool for transferring money and / or logging information.

“Blockchen is a volatile digital account book of financial transactions that can not only be programmed to record financial transactions, but everything about value.”

Common uses of Blockchain

Data sharing

Payment Processing and Money Transfer

Monitor supply chain

Copyright and royalty protection

Food Security

Irrevocable data backup

Medical record keeping

Application of Blockchain

Smart Contract

Cloud storage

Supply-chain communication and proof-proven

Paying employees

Electronic Voting

4. Robotic Process Automation or RPA

Robot process automation (or RPA) software is an emerging form of business process automation technology based on the belief of robots or artificial intelligence (AI) workers. .. these devices also automate interaction with GUI, and often repeat a set of user-generated display tasks.

Like AI and machine learning, Robot Process Automation, or RPA, is another technique that is automating jobs. RPA software is used to automate business processes such as interpreting applications, processing transactions, dealing with data, and even responding to email.

General use of RPA

Imitates human action:

Using a variety of applications and systems, imitates human execution of the repetition process.

Conducting repeated functions of high volume:

Robotics process automation can easily emulate the data from one system to the reinking of the data. It works like data entry, copying and pasting.

Do many things:

Operates many more complex tasks in many systems. This helps to process transactions, manipulate data and send reports.

‘Virtual’ system integration:

This automation system can transfer data between heterogeneous and legacy systems, rather than developing new data infrastructure, by connecting them at the user interface level.

Automated report generation:

Automation of data extraction to come with accurate, effective and timely reports.

Information verification:

Solving and cross-verifying data between different systems to validate and check information for providing compliance and auditing output.

Technical Debt Management:

Reducing the gap between the system, helping to reduce the technical loan by stopping the introduction of custom implementation.

Product Management:

This helps to bridge the gap between IT systems and related product management platforms by automated updates of both systems.

Quality assurance:

This can be beneficial for QA procedures which covers regression testing and automates the case of customer use.

Data migration:

Allows automated data migration via system, which is not possible to access traditional mediums such as documents, spreadsheets, or other source data files.

Gap Solution:

The robot fills the gap with the lack of automated process. This can include simple tasks like password reset, system reset, etc.

Revenue forecast:

Automatically update financial statements to estimate revenue forecast.

5. Edge Computing

To reduce leg computing and bandwidth usage, edge computing is a networking philosophy that focuses on bringing computing closer to the source of data. In simple words, Edge computing means running fewer processes in the cloud and moving those processes to local places, such as user computers, IoT devices or edge servers. Bring computation on the edge of the network, reduces the amount of long distance communication that must be between the client and the server.

Edge computing in IT is kept away from centralized and always-connected network segments as data-handling activities or deployment of other network operations, and towards individual sources of data capture, such as laptops, tablets or smartphones. Through this kind of network engineering, IT professionals expect the network to improve security and increase other network results.

Common uses of Edge Computing

Grid Edge Control and Analytics

Oil and Gas Remote Monitoring

Edge Video Orchestration

Traffic Management

Autonomous Vehicles

6. Augmented Reality and Virtual Reality

One of the biggest delusions in the world of augmented reality is the difference between augmented reality and virtual reality. Both are attracting very attention of the media and are promising tremendous growth. So what’s the difference between virtual reality vs augmented reality?

What is virtual reality?

Virtual reality (VR) is an artificial, computer-generated simulation or real-life environment or condition of entertainment. It dissolves the user by feeling that they are already experiencing the fake reality, primarily by stimulating their sight and hearing.

What is augmented reality?

Augmented Reality (AR) is a technology that combines computer-generating enhancement with an existing reality so that it can be made more meaningful through its ability to interact with it. AR is developed in the app and digital devices are used on mobile devices to blend in the real world in such a way that they enhance each other, but can be easily separated.

According to an article from Monster.com, demand for job candidates with VR knowledge is up to 37 percent, but potential employees are in short supply. That demand will only increase. In the VR market there are major players like Google, Samsung and Oculus, but there are a lot of startups and they are hiring – or trying to overcome the deficit. Special knowledge is required not to start in the VR. Basic programming skills and a forward thinking mindset can do a job, though other employers will also look for optics as skill set and hardware engineers.

7. Internet of Things (IoT)

The Internet of things, or IoT, is a system of interconnecting related computing devices, mechanical and digital machines, objects, animals or people that provide the ability to transfer data to a network without the need of unique identifier (UID) and human. . Human or human-to-computer interaction

As technology advancement, Internet of Things (IoT) is becoming part of our daily lives. as we know that so many people using mobile phones for communication. Smart glass, self-driving car and home automation is no longer a dream. According to the Motley Flowers and Forbes, here are some interesting facts about Internet of Things.

By 2021, IoT is expected to have an industry of $ 1.4 trillion, as companies invest in software, hardware and other services. According to General Electric, more than $ 60 billion investment in industrial IoT products and equipment is expected to be invested by 2030.

Application of Internet of Things

Smart home

Wearables

Smart City

Smart grids

Industrial internet

Connected car

Smart retail

Smart supply chain

Smart farming

8. Cyber Security

Cyber ​​security includes technologies, processes and controls that are designed to protect systems, networks and data from cyber attacks. Effective cyber security reduces the risk of cyber attacks and prevents unauthorized exploitation of systems, networks and technologies.

Three pillars in strong cyber security: implementing controls based on people, processes and technology. This three-dimensional approach helps organizations save themselves from organized attacks and general internal threats, such as accidental violation and human error.

As a proof of the strong need of cyber security professionals, the number of cyber security jobs is increasing three times faster than other technical jobs. However, when we talk about filling up those jobs, we are getting reduced. As a result, it was predicted that we would have 3.5 million unforced cyber security jobs by 2021.

Many cyber security jobs pay six-figure earnings, and roles can range from ethical hackers to security engineers to the chief security officer, who offers a promising career path for those who want to stay and stick with this domain.

Application of Cyber Security

Strong Authentication

Secure Email

Smart Cards

Virtual Private Networks

9. Cloud Computing

Cloud computing is shared by shared computer system resources and pool of high-level services, which can be rapidly provisioned on the Internet with minimal management effort. Cloud computing depends on the sharing of resources to achieve consistency of scale and economies of scale similar to public utility.

Simply put, cloud computing is a delivery of computing services – servers, storage, databases, networking, software, analytics, intelligence, and more and more Internet (“cloud”), which is rapidly developing economies of innovation, flexible resources and scale Offers. You usually pay only for the cloud services you use, which help reduce your operating costs, run your infrastructure more efficiently, and as needed to change your business is.

Types of cloud computing

Public cloud

Private cloud

Hybrid cloud

Types of Cloud Services:

Infrastructure as a service (IaaS)

Platform as a service (PaaS)

Serverless computing

Software as a service (SaaS)

10. DevOps

The term DevOps is generally considered to be a combination of concepts of development and operation. It is used to refer to the roles or processes in IT which bridge the various departments – usually the development and operation team – to achieve a certain project management philosophy, in which the development teams and a large business or other organization Communication between parts involves more efficiency.

Toolchain of DevOps

Coding – code development and review, source code management tools, code merging.

Building – continuous integration device, construction status.

Tests – Continued testing equipment that provide feedback on business risks.

Packaging – artifact store, application pre-station staging.

Release – Change Management, Release Approval, Release Automation.

Configuration – Infrastructure configuration and management, infrastructure in the form of code tools.

Monitoring – monitoring of applications performance, end-user experience.

Goals of DevOps

Better Deployment Frequency;

Fast time for the market;

The low failure rate of the new release;

Short lead time between reforms;

Fast time means for recovery (crashing or otherwise disabling existing system in case of new release).

11 Big Data

Big data is a word that describes the large amount of data – both structured and unstructured – which adds a business on a daily basis. But this is not the amount of data that is important. This is the organization that works with data that matters. Large data can be analyzed for insights that lead to better decision-making and strategic business moves.

Volume – Organizations collect data from a variety of sources, including business transactions, social media and sensor or machine data from the machine. In the past, collecting it was not a problem – but new technologies (such as Hadoop) have reduced the burden.

Speed – Data flows at an unprecedented speed and should be dealt with in a timely manner. RFID tags, sensors and smart metering are run in the near-real-time need to deal with torrents of data.

Variety – Data comes in all types of formats – structured in traditional databases, numeric data to unread text documents, email, video, audio, stock ticker data and financial transactions.

In SAS, we consider two additional dimensions when it talks of large data:

Variability – In addition to rising velocity and varieties of data, data flow with periodic peaks can be highly incompatible. Is there some trend in the social media? Managing data load of daily, seasonal and event-trigger peaks can be challenging. Even more with unstructured data

Complexity – Today’s data comes from many sources, making it difficult to link, match, change and replace data across the system. However, it is important to add or associate relationships, hierarchies and many data linkages, or your data can be quickly out of control.



Mohit Varma

Words can't define me, but I can tell you what I am right now, I am a Computer Science Engineer student,technical writer,coder,blogger,and tech enthusiast!!.Now I am studying at Thakur Shiv Kumar Singh Memorial Engineering College.

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