Data Science Trends 2019

Top 5 Data Science Trends To Watch In 2019

Data science is a vast discipline which includes several fields like artificial intelligence, Internet of Things, machine learning, and deep learning among others. It’s a compound mix of technology, data theorization, analytics and algorithm calculations for the purpose of finding resolutions for a wide range of business problems. Data science deployment and applications have been exponentially increasing thanks to relentless competition among businesses, emergence of innovative and more sophisticated technology, and of course, the rising popularity of data science itself.

The following trends are expected to dominate the field of data science in 2019:

1. Regulatory Schemes

The volume of data per second that is generated is mind boggling; this is chiefly driven by factors like IoT. This has also increased the threat of cyber-attacks – and we saw a slew of hacking incidents in 2017; the attacks are growing not just in number, but also in sophistication. Several high profile databases were breached, leading to major losses for financial institutions, businesses, and their customers. Data security is now of paramount importance, for this very reason. We can expect the regulatory environment to get stricter in 2019. The General Data Protection Regulation or GDPR, enforced in May 2018 in Europe, placed stringent conditions on the collection, management and sharing of personal data of European citizens, or if the company is based in the EU. Such regulations and protocols to ensure data security are expected to increase in number, and they will have a significant impact on the predictive models and analytic exercises in the coming years.

2. Artificial Intelligence and Intelligent Apps

AI is here to stay; currently, AI is in its infancy. But we are likely to see more advanced AI applications in the very near future, in a number of fields. Harnessing the true potential of AI will still not be a cakewalk, and more companies may invest more time and money in AI R&D. We can expect to see a greater number of apps developed with machine learning, artificial intelligence, and other technologies; it is highly likely that automated machine learning will become more commonplace; hardware will be developed especially for the training and implementation of deep learning. By incorporating AI, decision making capabilities can be improved, leading to enhanced business experience. New applications may incorporate AI in some form or other to enhance the functioning of their programs, leading to a surge in the number of intelligent apps developed; we may also see more intelligent devices flooding the market.

Read >> How Artificial Intelligence (AI) to Improve Customer Experience Management Efforts 

3. Virtual Representations of Real-World Objects and Real-time innovations

It is expected that in 2019, AI will power digital representations of actual physical objects, and this will be utilized for solving real life business problems in companies throughout the world. With technology advancing in leaps and bounds, the speed of real time innovations is also expected to increase rapidly. Developers are likely to use more of machine learning and neural networks in apps that will be rolled out in the coming year. Applications powered by virtual reality and augmented reality are already bringing significant transformation in user experiences, and data collection. Industry experts opine that we will see even more breakthroughs in this arena, and we will also witness enhanced interactions between people and machines – of course, this will also result in increased expectations from machines and digital systems.

4. Edge Computing

With the proliferation of IoT increasing by leaps and bounds, edge computing will also become more popular. Millions of devices and sensors collect data for analysis, and businesses are performing more data processing and analysis at the edge – or close to the origin source. It is expected that edge computing will be implemented increasingly, so as to maintain proximity to the information source.in combination with cloud technology, edge computing will deliver a synchronized framework that mimics a service-oriented prototype. Cloud pricing structures of the near future are expected to serve specific analytics workloads and contribute to a higher spending growth on cloud 5 times more than on in-house analytics.

5.Blockchain

Bitcoin is a Cryptocurrency that has the digital world in a tizzy; the technology that powers it, is Blockchain. This technology uses a highly secure ledger, and has several applications apart from Cryptocurrency. For example, it has the capability of recording numerous transactions in detail. Blockchain technology may impact data security positively and tremendously. We may see innovative security protocols that emulate this technology in 2019 to ensure greater safety of data.

To Conclude

Developers and data scientists will continue to innovate, to deliver better business experiences, seeing as these trends are set to continue. Data Science will continue to grow in popularity and we could see a plethora of data science applications being developed and implemented in 2019. With the ever increasing interlinking of the physical and digital worlds, digital experiences are likely to get intricately intertwined with human experience. We may well be on the cusp of unforeseen exposure and development of the field of data science, as all the trends mentioned above seem here to stay for some time.