Top 5 Data Science Trends in 2018

Data Science in today’s world is a combination of various functions – AI, Deep Learning (real and hyped progress), Quantum Computing, Big Data, IoT, and many more such applications which are used together as a network. 2017 was dominated by advances in the AI space which had taken over from Big Data. Data has become popular due to the open source regime which is slowly chipping away at the market and technology shares of established names like Oracle and  Microsoft. With the ever-increasing popularity of newer and scalable programs, let us see the top trends to expect in 2018.

  • Regulation – The awaited impact-event will be GDPR (European General Data Protection Regulation) which will become enforceable on May 25, 2018. This regulation will affect data science practice in three areas – limits to be applied on data processing and consumer profiling, “automated decision making” and the right to an explanation for that, and feeding in biases and discrimination in automated decisions. The measures under this act were approved by the European Parliament on April 27, 2016, and will go into effect on May 25, 2018. The law will focus on the new rules on collection and management of personally identifiable information (PII) of EU citizens. Implementing these rules will bring broad changes in the big data modelling and in creating predictive models.
  • Artificial Intelligence – According to Garter’s list of Top 10 tech trends in Big Data, is laying the foundation of AI across organisations. It will remain a major challenge and work plan to follow through till at least 2020 as significant investment in skills, processes and tools will be required to exploit these techniques.
  • Intelligent Apps – These will be created and used with an aim to enhance human activity and effort and mostly not replace it. Augmented analytics is a strategic growth area in which machine learning will be widely used to automate data preparation, insight discovery, and sharing for a large range of business users, operational workers and citizen data scientists.
  • Virtual Representations of Real-World Objects or Systems – Digital representations of the real-life objects will be a common reality and their inter-linkages will help in checking the cause and effect changes for improving the operations and value. It is predicted by that over time digital twins of every physical reality will be available and infused with AI capabilities to enable simulation, operation and analysis. This will particularly help in fields of city planning, digital marketing, healthcare and industrial planning.
  • Cloud to the Edge – Edge computing works to maintain the closeness of processing, content collection and delivery close to the source of information. This helps in reducing issues to latency, bandwidth, connectivity. Garter predicts that pairing this strategy with cloud computing will give the best of both the worlds to create a service-oriented model and a centralized model and coordination structure.

While many trends will take a long while to cultivate from its conceptual stage to a working philosophy, these trends will lead the way for future innovations.

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