As technology continues to advance so will the field of data science. Much of 2018 was viewed as the year of data breaches and leaks; this year however, will be known for technological disruption and use of Artificial Intelligence. In 2019 we will also see a focus on maturing technologies. Here are some of the top data science trends for 2019:
Reinforcement Learning: During 2019 there will be a resurgence of reinforcement learning. Even though this is best described as a “human-like learning behavior,” we will see its use in data science through statistics and algorithms. Concepts using reinforcement learning will start to turn into actual products as well.
Augmented Data Management: This latest trend in data science is a game changer for the industry. According to Information Age, “Augmented data management utilises machine learning capabilities and AI technology to make data management categories including data quality, master data management, metadata management, data integration as well as database management systems (DBMSs) self-configuring and self-tuning.” Thanks to augmented data management, more individuals will be able to use data. It also gives high-level data scientists the opportunity to work on more important tasks.
Data Security and Privacy: In 2018 data security and privacy were huge issues and this year we will continue to hear about it on a regular basis. In May of 2018, the EU put the General Data Protection Regulation into place, creating a direct impact on data science. The two main points of this regulation are data privacy and right to explanation. Large fines will be placed on companies that mishandled personal data and automated decisions must be explainable according to the new regulations. One of the biggest challenges of these new rules is that many companies are still trying to figure them out. In 2019, we will see how the EU decides to enforce the new rules.
Explainable AI: We’ve seen a great increase in the amount of AI used in data analytics and we will continue to see its use flourish. Artificial Intelligence is used in data management, but, there are a lot of questions surrounding how AI comes to certain conclusions. Luckily, explainable AI gives us the answers we need; it’s able to generate explanations of data models that are easily understood by data scientists.