Connected technologies are impacting how people and systems communicate with each other, how engineering and construction projects are managed, and how products and machines are made. These disruptive technologies are also changing the employment landscape, particularly for data scientists and data analysts in engineering.
A glimpse into the future of engineering is visible with every new technology that comes to market. This is because the insights derived from the work of data scientists and data analysts are at the epicenter of transformative innovations taking place throughout energy, telecommunications, manufacturing, finance, technology, and other sectors.
Averaging over 30% annual growth, insights-driven organizations, so named by Forrester, are expected to earn $1.8 trillion by 2021, according to the business and technology research firm. As a result, knowledgeable professionals who are skilled in extracting information and insights from data are in high demand: data scientist tops the list of Glassdoor’s “50 Best Jobs in America for 2019.”
Powering the Future of Engineering
Data scientists and data analysts in engineering work with a wide range of systems, including cellular communications towers, power grids, and electrical infrastructure that runs transportation systems. It’s common for data scientists and data analysts to work with engineers, such as systems engineers, to improve existing technology.
Data scientists and data analysts will help power the future of engineering by leveraging the fifth-generation (5G) network, artificial intelligence (AI), and digital twin technologies in the engineering and construction industry. For data science professionals pursuing careers in engineering, staying in step with these technology trends is key to advancing in their careers.
5G: The Fifth-Generation Network
Historically, communications infrastructure improvements have been a boon to new markets; consider the rise of industry giants like Amazon and Apple in the digital age. Developments in communications infrastructure are also a factor in driving the digital economy’s growth at a median rate of 5.6%, according to the U.S. Bureau of Economic Analysis. Predictions are that 5G will spark innovation in smartphones, devices powered by the internet of things (IoT), industrial robotics, and smart cars. The percentage of Americans who own smartphones has reached 77%, according to the Pew Research Center. So as 5G networks are launched, expect telecommunications companies to step up competition with each other for the leadership position in the market.
5G will enable faster data transmission — at roughly 20 times faster than 4G, 5G will enable you to download full-length movies in well under 20 seconds, by some estimates. And 5G has the potential to make a great impact on society.
What does the future of engineering in a 5G world mean for data scientists and data analysts? It provides opportunities for them to help build the backbone of the worldwide 5G network. Because data production will vastly accelerate, professionals will be needed to make sense of the data quickly and accurately. This creates opportunities for data scientists and data analysts.
AI in Engineering and Construction
McKinsey & Company values the engineering and construction industry at $10 trillion a year. Yet, AI adoption in this industry is tepid compared with other industries, such as manufacturing. But adoption trends are promising: 59% of organizations are in the information-gathering stages of their AI strategies, and the rest are either adopting AI solutions or developing pilot programs, according to a Gartner survey.
Given AI’s benefits in the industry — schedule management, project planning, data collection — expect increased industry-wide adoption of AI over the long term. In the future of engineering, deep learning, an AI branch, will offer engineering and construction companies the ability to refine quality control. For example, a deep-learning application can potentially analyze drone images to determine construction defects. In another example, AI can provide key insights into how experts on construction sites work to help trainees understand and make modifications to their movements to maximize safety and productivity.
Applications such as these will improve decision-making for owners and contractors who want to constantly optimize their building designs, enhance worker performance, and provide better environments for people. AI will also help construction companies create better business models, with a focus on improved customer experiences. These benefits will drive digital initiatives in engineering and construction through 2025, according to Gartner.
The concept of a digital twin dates back to 2002. NASA used a forerunner to this type of pairing technology to rescue the Apollo 13 mission. While the idea has been on the minds of engineers for decades, only now is digital twin technology cost-effective to implement and use — thanks to IoT, machine intelligence, and connectivity. Today, experts predict that digital twin technology can improve the cycle times of critical processes by 30%, according to a recent Forbes article.
What is a digital twin? Relevant definitions include a virtual representation of a real product and a virtual simulation of a machine. To understand what it is, consider what it is not. In the engineering field, computer-aided design (CAD) models are typically used in the design phase to represent a physical object, such as a component in a machine. For example, a CAD model can help with visualizing pieces of a larger puzzle in 3-D, allowing for instant design modification before manufacturing. A digital twin goes beyond that capability. Add information about failures, stresses, maintenance schedules, and other data, and then combine it with the speed of communications technology, and you get something else beyond a CAD model: you get a digital twin.
In engineering and construction, a digital twin can provide key insights on the performance of individual components or entire systems, which then enable professionals to implement critical design changes in the physical world in near real time. It has the potential of maximizing safety, extending the life of equipment, uncovering inefficient processes and functionalities, speeding up recovery from downtime, and minimizing costs through predictive maintenance. The savings potential for the engineering and construction industry is enormous. Take IoT, for example, which creates an environment where connected technologies and sensors — estimated to reach 21 billion by 2020, according to Gartner — are within reach with just a swipe or a tap of a finger. With digital twins for billions of things, savings opportunities are exponential.
Career Growth in the Future of Engineering
The U.S. Bureau of Labor Statistics (BLS), under the category of computer and information research scientists, projects 19% growth in employment from 2016 to 2026, much higher than the average. The BLS reports an annual median salary of $114,520, as of 2017.
In addition to technical knowledge, candidates need strong business acumen, critical thinking skills, an ability to understand complex problems, and an ability to extract meaningful information from structured and unstructured data to achieve breakthrough results.
Become a Leader in the Future of Engineering
If you’re a data professional looking to lead at the highest level, consider Maryville University’s online Master of Science in Data Science program. The curriculum is built with input from top employers and geared to prepare students with the most in-demand skills in modern data science. The program provides students with practical know-how in computer programming in a variety of languages, machine learning, predictive modeling, and big data analytics to impact and influence the future of engineering. Learn more about the MSDSCI program and all of Maryville University’s Computer Science degrees.