As we near the end of 2021, the industry is heating up with predictions on what’s in store for 2022. In a recent Forbes article, Bernard Marr tackled some emerging data science trends, including: 

Small Data and TinyML

As we’ve discussed in a previous APEX of Innovation post, small data is becoming an increasingly important part of enterprise analytics strategy. Marr believes the latter is critical in situations where time, bandwidth, or energy expenditures are particularly vital and offers self-driving cars as an example. When trying to avoid a crash in an emergency, these vehicles cannot rely on a centralized cloud server but rather need intelligence at the edge to make the best decision as fast as possible. In 2022, expect to see more small data and increased usage of TinyML—machine learning algorithms that can run on low-powered hardware, as close to the edge as possible. 

Data-Driven Customer Experiences 

Data-driven customer experiences is another topic near and dear to our hearts at the APEX of Innovation. Marr predicts that finding new ways to leverage customer data for better, more personalized experiences will be a primary focus for many data scientists throughout 2022. 

Deepfakes, Generative AI, and Synthetic Data 

To date, deepfakes and generative AI have been seen predominantly on social media and in the entertainment industry. Next year, Marr believes that will begin to change as the technology expands to new sectors and use cases. For example, generative AI has the potential to create synthetic faces to train other ML algorithms, mitigating the privacy concerns and ethical issues associated with using real people’s faces. 

Convergence 

Another of Marr’s predictions is that 2022 will bring an increased convergence of trends such as AI, the IoT, cloud computing, and 5G. As these transformative technologies are combined, they will augment each other’s strengths and open up new possibilities for data scientists to explore. 

AutoML 

AutoML has significant potential when it comes to the democratization of data science. Expect developers to be increasingly focused on creating tools and platforms for subject matter experts to develop their own ML apps in the year ahead.

For more on these five trends and how they may play out as we head into 2022, take a look at Marr’s piece in its entirety.