Top 5 Tech Industry Trends Shaping IT
The technology we use on a daily basis is rapidly changing. From hyper-fast 5G networks to advanced cloud databases, we’re always reading about new ways to automate our lives in the home and in business operations.
As innovation accelerates companies’ needs to automate their business and align their departments around new platforms and technologies, the need to hire in IT is also increasing.
Before we take a look at the technologies that are transforming the IT industry and shaping the tech roles of tomorrow, let’s look at the most in-demand tech jobs this year.
Most In-Demand Tech Jobs in 2020
The tech industry of 2019 was quite similar to the landscape we saw in 2018, with the demand for IT professionals in cybersecurity, software development and data analytics as top priorities.
More and more often, traditional companies are beginning to resemble tech companies in how they hire and shape their departments and priorities, and this trend will likely continue throughout the next year, according to Sarah Stoddard, a community expert at Glassdoor.
"As employers across diverse industries, from health care to finance to automotive and more, continue to implement various technologies to streamline workflows and boost business, the demand for top-notch workers who have a balance of technical and soft skills will continue to rise."
1. Artificial Intelligence (AI) Architect
Average Salary: $143,750
In 2019, studies showed that AI architects would be one of the fastest-growing jobs, and it seems the demand is not slowing down in 2020.
IT architecture is why the largest tech companies enjoy their tremendous growth. If they want to maintain their momentum, then they must implement AI into their architecture while minimizing disruption.
2. Cloud Architect
Average Salary: $141,750
Cloud architects manage the cloud computing architecture of an organization, especially in large companies or government institutions that have complex cloud requirements. That’s because architecture encompasses everything to do with cloud computing on the front end, as well as storage, servers, delivery and the networks required to manage cloud storage.
3. Data Engineer
Average Salary: $163,350
Data engineering is associated with organizing data and databases — mainly, data delivery, storage and processing. The biggest responsibility of a data engineer is to provide a reliable infrastructure for data analytics. Hence, for any data-driven organization, it is vital to employ data engineers in order to be on the top.
4. Mobile Developer
Average Salary: $146,500
A mobile developer is skilled in developing a software system for smartphones. As mobile usage continues to surpass the time users spend on desktop, the need for mobile developers for e-commerce and the need to create more engaging mobile experiences are on the rise.
5. Network Security Engineer
Average Salary: $119,750
A network security engineer’s responsibilities include building networks consisting of switches, routers, firewalls and VPNs that are defensive against breaches. The network’s safety is this engineer’s main priority. In order to be successful in the role, you must have considerable analytical prowess, technical ability and problem-solving skills to ensure the network’s security is sound.
Security engineering positions are now a necessity in the age of high-profile data breaches in the past decade. Hackers and malware are always present — they can breach your network and wreak havoc on your databases and servers by corrupting and stealing sensitive data. The demand for specialized security engineers who can quickly identify and resolve vulnerabilities is likely to continue increasing for the foreseeable future. According to a Dice report, these engineers are “very hirable if they possess certifications such as CompTIA Security+, Certified Information Systems Security Professional (CISSP), and GIAC Certified Incident Handler (GCIH).”
Top Business Tech Trends to Watch in 2020
AI-as-a-service is becoming especially popular in the marketing industry. Many marketers already use Google’s AI and machine learning algorithms for data analytics to track website visitors. AI is also being used via chatbot programs to create a more human-like interaction and experience when users land on a company’s site.
There are many benefits to AI-as-a-service, including:
- Natural language processing
- Data analytics
- Consumer product recommendations and behavior forecasting
- Fraud detection
- Chatbots for customer service
- Managing and updating databases
We can expect more AI applications and dynamic platforms to hit the market this year. They will help businesses to streamline pulling and transferring data, and businesses can simply pay for the computer resources and algorithms as they're used without having to hire a dedicated AI architect.
To date, these AI platforms are owned by Microsoft, Google and Amazon, and are relatively broad in scope. In 2019, this often translated into expensive custom engineering implementations when the AI platforms needed to be applied to organizational-specific tasks — something that will likely change in 2020. This year, expect to see a larger and constantly growing pool of companies that provide AI-as-a-service platforms. This will bring forth more tailored services and applications for specialized tasks.
#4 5G Data Networks
5G data networks have been in the works for nearly a decade, but in 2019, they finally became reality. We can expect to see 5G networks incorporated in the latest desktops, smartphones and tablets to harness the full capabilities of the next generation in wireless connectivity.
Carriers are already starting to roll out 5G in select U.S. cities, and a much more comprehensive roll out is forecasted for 2020.
5G will augment your mobile experience when streaming on smartphones with minimal latency, faster download speeds and enhanced communication between devices and wireless networks.
While there are only a few 5G-compatible devices are on the market right now — most notably Apple’s iPhone 11 and the latest Android mobile phones — we will likely see more devices in February 2020 when the Samsung Galaxy S11 hits stores with a full range of 5G upgrades available.
#3 Edge Computing
Edge computing involves processing data and content collection/delivery that is “placed closer to the sources, repositories and consumers of the information.”
This computing technology reduces latency and allows for more exceptional capabilities at the edge of a connection. For example, 5.6 billion Internet of Things (IoT) devices will utilize edge computing in 2020.
“Much of the current focus on edge computing comes from the need for IoT systems to deliver disconnected or distributed capabilities into the embedded IoT world for specific industries such as manufacturing or retail,” says Brian Burke, Gartner vice president of Research, in a 2019 tech trends press release. “However, edge computing will become a dominant factor across virtually all industries and use cases as the edge is empowered with increasingly more sophisticated and specialized compute resources and more data storage. Complex edge devices, including robots, drones, autonomous vehicles and operational systems, will accelerate this shift.”
#2 Cloud Computing
At its most basic definition, cloud computing is the delivery of computing services. This includes storage, servers, networking, databases, software, analytics and business intelligence — using a cloud hosted online. It allows for the flexible use of resources and increases internal innovation in scaling operations.
One of the key benefits of cloud computing services is its affordability. No longer do you need to bog down your own infrastructure with more data and inevitably be forced to expand your database — now you can simply “put it up on the cloud.”
The Benefits of Cloud Computing
Cloud computing is miles from the traditional way businesses thought about IT resources just 25 years ago. Cloud computing offers:
1. Affordable Pricing:
The first thing you will notice about cloud computing is that it is much more affordable than buying new hardware and software and setting up your own in-house data centers. The cloud is the best solution to scale rapidly because it eliminates the need for data centers.
2. Productivity Boosts:
No longer focusing on hardware maintenance and updates means your staff can instead focus on higher-priority tasks in regular business operations.
3. Instant Deployment
Through the cloud, you can launch new systems around the world instantly. For example, AWS has its infrastructure set up around the world. So, on the AWS cloud, you can launch applications simultaneously on multiple continents. This is crucial in positioning applications closer to end-users in order to provide the optimal user experience.
4. Reliable Security
Cloud providers have many policies and advanced technologies that reinforce your infrastructure’s overall security. The added layer of security for sensitive data and the infrastructure are worth the investment.
Indeed, organizations across all industries are embracing the cloud, and its benefits for everything from increased efficiency in data transfers to infrastructure security are becoming invaluable to companies in 2020. For example, in healthcare, the cloud is working in tandem with machine learning technology to provide personalized treatments for patients.
#1 Machine Learning
Machine learning is a computer’s ability to learn autonomously by analyzing data points and tracking repeating patterns. For example, Facebook uses machine learning to analyze your profile based on shares, likes and comments to understand how you’re connected to everyone in your list of friends. This data tells Facebook how close you are with that person, which enables Facebook to prioritize that person’s latest posts at the top of your newsfeed.
Machine learning is used in the following industries, among others:
Marketing and Sales
The most noticeable development in machine learning for marketing is Amazon and other e-commerce sites. On the checkout page, Amazon recommends similar items or other products you may be interested in. Machine learning has undeniably become the number-one driver of personalization in marketing and sales. As mobile devices increasingly become our preferred form of shopping, surely we will see a boom in apps tailored to powering the collection of new datasets to inspire more personalized experiences that drive online revenue.
Public institutions are using machine learning to enhance their ability to maintain public safety. Databases on a local and national scale can be used to retrieve data on a target to pull public records. Government agencies are also using machine learning for sensor data analysis as a way to increase efficiency in reducing identity theft. While there is some concern in how governments will be using machine learning, and inevitably more advanced forms of AI, it’s pushing the narrative of increased standards of ethics, which is having an impact on the private sector as well.
When it comes to healthcare, machine learning is making a serious impact as a fast-growing trend in the industry. Its implementation is driven by the introduction of wearable devices/sensors that instantly send data on a patient’s vital signs. Nurses and doctors can access this data to assess a patient’s health in real time.
Some doctors think things are moving too fast, but the rate of progress keeps increasing, which is how “it should be” for many. “AI is the future of healthcare,” said Fatima Paruk, CMO of Allscripts Analytics, in 2017.
The finance industry is utilizing machine learning to identify crucial insights from data to detect and prevent credit fraud. Data insights from machine learning can also identify opportunities for investment, providing guidance on when to trade.
Machine learning is enhancing the oil and gas industry’s efforts to uncover new energy sources. These sources have materials that must be analyzed, and machine learning allows for more efficient, streamlined oil distribution, relieving strain on budgets. That’s because machine learning significantly increases accuracy when drilling holes, which means there will be 10 percent fewer dry wellheads.
The ability to identify patterns and trends through data is vital for the speedy transportation of goods. The industry’s success is constantly improving the routes taken and conducting a risk assessment of what factors may hurt profits. That’s why data analysis and the power of machine learning allow truckers to deliver packages to our homes and food to our grocery stores.
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