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Data Science Trends in 2018

By   /  November 21, 2017  /  No Comments

The Data Science Trends for 2018 are largely a continuation of some of the biggest trends of 2017 including Big Data, Artificial Intelligence (AI), Machine Learning (ML), along with some newer technologies like Blockchain, Edge Computing, Serverless Computing, Digital Twins, and others that employ various practices and techniques within the Data Science industry.

The Dataconomy article titled The Future of Big Data Is Open Source aptly captures the industry buzz that dominated the last part of 2016 and the entire 2017. Then, Big Data and Data Science were the biggest industry buzzwords, but a lot has changed since then. In 2016, and 2017, Big Data was a market differentiator for businesses, and continues to be. Now, as we enter 2018, there are numerous new technologies that will coordinate within the greater foundations of Data Science and Big Data, and expand such industries into new spaces that are only beginning to be understood and appreciated.

The 2018 Technology Trends

One of most common themes of discussion in industry literature since August 2017 has been Gartner’s Top 10 Strategic Technology Trends for 2018. A recurring theme in the 2018 tech trends is the mingling of the “physical & digital worlds,” within the container of Data Science, AI, and Machine Learning. According to Gartner, the self-learning (ML-powered) intelligent systems will continue to reign supreme in the technology marathon through 2020.

Many industry observers have echoed Gartner’s No. 1 prediction that most IT applications will embrace Artificial Intelligence in one form or another in the next several years. The Journal responds with a strong admission of this truth in the article titled AI, Merging of Digital and Physical Worlds Among Top 10 Tech Trends for 2018.

In fact, the top four tech trends in Gartner’s top 10 list are related to intelligent machines or systems.  The first three trends, AI, intelligent apps, and intelligent things are closely followed by digital twins, which refer to the world of physical responses through digital sensors or Internet of Things (IoT). The news flash titled The Top 10 Tech Trends for 2018 indicates that global enterprises will cash in on this Artificial Intelligence wave in 2018 and use it to create a market differentiation. The disruptive capabilities of AI, ML, and IoT have been highlighted in this review of nest year’s tech trends.


The Intelligent Digital Mesh

The Forbes blog post titled Explore the Gartner Top 10 Strategic Technology Trends for 2018 indicates that now healthcare providers will seriously look into the possibility of using Machine Learning in medical diagnostic systems to enhance patient care. This post sums up Gartner’s “Intelligent Digital Mesh” as the meeting of the physical and digital worlds, where humans, machines, data, and services are entwined into a mesh.

Forecasts for the Data Science Industry

Gartner’s Top 10 Strategic Technology Trends for 2018 gives a good overview of many of the top Data Science trends for 2018. As businesses and services aim more for the “connected world,” the overlapping of the physical and digital layers around us will probably gain more relevance.

Data Science Trend 1 – Artificial Intelligence: The widespread adoption of Artificial Intelligence into all business systems and decision-making applications. According to Gartner, 59 percent of organizations are still building their enterprise AI strategies while the remaining 41 percent of the organizations have already made the plunge.

Data Science Trend 2 – Smart Apps: The next several years will witness a steady rise in AI-driven apps and services. All managed software platforms like the ERP are currently on a race for AI integration in their existing systems for enhanced performance and value addition. This trend includes the use of digital assistants and virtual services.

Data Science Trend 3 – Intelligent Things: The Intelligent Things are semi-robotic, smarter versions of regular gadgets and equipments to make our lives easy. They will continue to expand at ever greater rates and in all parts of our lives.

Data Science Trend 4 – Digital Twins: Digital Twins will bring together the connected world of sensors and humans. This technology trend will further the case of mechanized asset management.

“In the context of IoT, digital twins are linked to real-world objects and offer information on the state of the counterparts, respond to changes, improve operations and add value.”

Data Science Trend 5 – Edge Computing: Edge Computing “describes a computing topology in which information processing and content collection and delivery are placed closer to the sources of this information.” Such technology is directly related to the Internet of Things will expand with far-reaching implication on “sources of information.”

Data Science Trend 6 – Intelligent Platforms: The conversational platform pushes machine intelligence up a notch, where human expectations from digital systems will significantly rise. These systems, however, are expected to deliver results based on the event models and APIs they are fed with.

Data Science Trend 7 – Augmented Reality: The Immersive Experience related to augmented reality (AR) and virtual reality (VR) is already changing the world around us. The human-machine interaction will improve as research breakthroughs in AR and VR come about.

Data Science Trend 8 – Blockchain: Blockchain will become a much more important technology for businesses across the globe. Very simply put, Blockchain enables un-trusted parties to engage in transactions. Blockchain holds promise for many industry sectors like the finance, healthcare, and content delivery.  This technology is still maturing.

Data Science Trend 9 – Event Driven Techs: Events drive businesses. This trend is expected to bring about some revolutionary changes to joint stakeholders in businesses.

“Some business events or combinations of events constitute business moments — a detected situation that calls for some specific business action. The most consequential business moments are those that have implications for multiple parties, such as separate applications, lines of business or partners.”

Data Science Trend 10 – Security: In an ever more complex security environment of digital businesses, a sophisticated tech strategy known as “Continuous Adaptive Risk and Trust Assessment” (CARTA) will enable better decision making with adaptive responses to digital business. The basic premise of CARTA is trust.

Also review McKinsey’s Report on the Ten IT-enabled Business Trends for the Decade Ahead, which talks about three other technologies shaping the current business world, namely the Cloud, automated knowledge work, and the mobile platform. These three trends have made the most impact on modern digital businesses in the recent years.

The overlapping of the physical and the digital world gain new meaning in the context of these three technologies. This report also indicates that social platforms make a powerful contribution in digital businesses. The data collected from the combined social channels make a significant difference to business output.

It is not out of context to mention the Gartner release titled 5 Trends in Cybersecurity for 2017 and 2018, which makes a solid case for security concerns in Cloud environments. This article assumes more significance at a time when global businesses are aiming for Serverless Computing – a move away from on-premise to hosted Data Management.

Is the Data Science Industry Ready for These Technologies?

According to KDNugget’s post titled Businesses Will Need One Million Data Scientists by 2018, IDC has predicted a steep shortage of 181,000 Data Scientists in 2018. The industry is racing ahead of time so far as newer and better technology trends are concerned, but does it have sufficient manpower to nurture and apply these technologies to real-world businesses? Are the current Data Scientists trained to handle “Intelligent Analytics”? Are humans and the ever-growing number of smart devices capable of working with each other?

The same concern has been expressed in this fascinating McKinsey Report, Big Data: The Next Frontier for Innovation. When Big Data began entering the mainstream business world, many businesses were thoroughly unprepared and unequipped to make the best use of this advanced technology. Similarly, some global businesses are likely not ready to handle the new technologies that are slated to surface and be major Data Science trends for 2018. There is a dearth of technologies, machines, and devices in the digital business world of today, but is the business manpower capable of making use of these fascinating technologies and smart devices surrounding them?

In the AMA publication titled Data Science is the Latest In-Demand Skill Set For Marketing, the clear indication is that enterprises are increasingly recruiting hires who not only have domain knowledge such as marketing but also advanced, Data Analytics skills without which they cannot do justice to their jobs in a data-driven business environment.

 

Photo Credit: ranjith Ravindran/Shutterstock.com

About the author

Paramita Ghosh has over two and a half decades of business writing experience, much of which has been writing for technology and business domains. She has written extensively for a broad range of industries, including but not limited to data management and data technologies. Paramita has also contributed to blended learning projects. She received her M.A. degree in English Literature in 1984 from Jadavpur University in India, and embarked on her career in the United States in 1989 after completing professional coursework. Having ghostwritten and authored hundreds of articles, blog posts, white papers, case studies, marketing content, and learning modules, Paramita has included authorship of one or two books on the business of business writing as part of her post-retirement projects. She thinks her professional strength is “lifelong learning.”

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