Top 10 Technologies to Master in 2018

Virtual and Augmented Reality

"When we look at projected trends (paywall) for both AR and VR technologies combined between 2016 and 2020, the figure skyrockets to a potential $215 billion in 2021 if adoption rates are high," wrote Forbes.

Big Data

The fintech renaissance

According to Fortune, in 2018, one must look for biometrics such as facial recognition, voice ID, and fingerprints to help make shopping far quicker —by eliminating the need to swipe a credit card at checkout, for instance. "Instead, you will be able to verify your identity for a merchant scanning your eyes with your smartphone, in what’s known as a retinal payment. A bold clairvoyant could even predict that some major retailers will hop on the cryptocurrency bandwagon and issue their own secure currency," added the publication.

Digital Twins 

According to Forbes, a digital twin is a virtual model of a process, product or service. This pairing of the virtual and physical worlds allows analysis of data and monitoring of systems to head off problems before they even occur, prevent downtime, develop new opportunities and even plan for the future by using simulations.

Moreover, digital twins integrate artificial intelligencemachine learning and software analytics with data to create living digital simulation models that update and change as their physical counterparts change. A digital twin continuously learns and updates itself from multiple sources to represent its near real-time status, working condition or position. This learning system, learns from itself, using sensor data that conveys various aspects of its operating condition; from human experts, such as engineers with deep and relevant industry domain knowledge; from other similar machines; from other similar fleets of machines; and from the larger systems and environment in which it may be a part of. A digital twin also integrates historical data from past machine usage to factor into its digital model.

Robotic Process Automation

In traditional workflow automation tools, a software developer produces a list of actions to automate a task and interface to the back-end system using internal application programming interfaces (APIs) or dedicated scripting language. In contrast, RPA systems develop the action list by watching the user perform that task in the application's graphical user interface (GUI), and then perform the automation by repeating those tasks directly in the GUI. This can lower the barrier to use of automation in products that might not otherwise feature APIs for this purpose.

RPA tools have strong technical similarities to graphical user interface testing tools. These tools also automate interactions with the GUI, and often do so by repeating a set of demonstration actions performed by a user. RPA tools differ from such systems including features that allow data to be handled in and between multiple applications, for instance, receiving email containing an invoice, extracting the data, and then typing that into a bookkeeping system. The data manipulation aspect is not something one would normally find in a testing tool.

Blockchain

"Originally devised for the digital currencyBitcoin,  (Buy Bitcoin) the tech community is now finding other potential uses for the technology. Bitcoin has been called “digital gold,” and for a good reason. To date, the total value of the currency is close to $9 billion US. And blockchains can make other types of digital value. Like the internet (or your car), you don’t need to know how the blockchain works to use it. However, having a basic knowledge of this new technology shows why it’s considered revolutionary," wrote blockgeeks.com.

DevOps

is a software engineering culture and practice that aims at unifying software development (Dev) and software operation (Ops). The main characteristic of the DevOps movement is to strongly advocate automation and monitoring at all steps of software construction, from integration, testing, releasing to deployment and infrastructure management. DevOps aims at shorter development cycles, increased deployment frequency, and more dependable releases, in close alignment with business objectives.

AI and Machine Learning

Chatbots

Intelligent Apps