The 4 Hottest Trends in Data Science for 2020

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Context

Over the past 5 years, companys in various industries have started their digital transformation. In other words, these companys are turning themselves into data-driven enterprises that making managerial and strategic decisions based on actual data rather than intuition or observation alone using advanced data technology. Such a trend of data integration has grown by over four times in the past 5 years according to Google Search Trends.

Google search popularity of “Data Science” over the past 5 years.

Four Trends of Data Science in 2020

As data science is becoming increasingly popular and business environment is constantly changing, the need for data innovation is more demanding. The following four trends will be the most popular in 2020.

Automated Data Science

In the data science process, data manipulation, especially cleaning and exploring data, requires much time-consuming manual work. However, the situation has gradually improved due to the rise of automated data science. For example. new deep learning techniques like Convolutional and Recurrent Neural Networks free people from manual feature design. In the field of machine learning, AutoML has also been created to automate model design and training. All these new tools makes data science cheaper and more assessable to the public.

Data Privacy and Security

Today, people are crowded with massively data with really no guarantee on anonymousness, data that are so personal and real that people feel insecure for their lives are being scrutinized by the known and more and more reluctant to offer them to enterprises. While the data science techonology is evolving, the transformation of data privacy and security should also catches up.

Super-sized Data Science in the Cloud

With the exploding data were accumulated over the past decades, cloud computing offers the opportunity for people to store, access, and analyze large size data. Some big cloud vendors includes Amazon Web Services (AWS) and Google Cloud.

Natural Language Processing

The development of Natural Language Processing(NLP) is a very powerful tool that can transform huge datastores of text into numerical data for analysis. With NLP, We now can analyze datasets that are much more complex such as buyers’ reviews.

Author

George Seif

• Position: Machine Learning Engineer

• Specialization: Machine Learning and Artificial Intelligence

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