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Data Science: Four Trends in 2020
Data Science is a combination of techniques, methods and algorithms for data collection, processing, analyzing, and predicting. It is directly related to artificial intelligence, data mining, and big data.
Four trends we are seeing this year in Data Science include:
Explainability – A major complaint of Machine Learning algorithms has been that the results are often unexplainable in terms of the logic and rationale used to derive a particular conclusion and are often difficult for other researchers to reproduce exactly. Accenture predicts that explainable AI is on the near-term horizon. Accenture predicts that explainability will become a necessary requirement before AI algorithms can be fully trusted.
Natural Language Processing (NLP) – AI tools are being made easier to use. In particular, expect conversational analytics, the use of a natural language interface, to become much more common and to boost the adoption of analytics and business intelligence tools.
Cloud-based Big Science – Processing large data sets require large amounts of processing power often in bursts. Computations can be very intense for short periods followed by inactivity. Cloud computing fits that scenario. With cloud computing, large capacity of processing power and storage can be easily made available quickly and then shut down when no longer needed.
Privacy and Security – In the last few years, data breaches have exposed massive amounts of personal and financial data. As a result, significant development is being made to create tools and algorithms that can better ensure data security and privacy.
