These 5 trends will redefine data science for 2022 and beyond

Today, its importance to the world of business and commerce is well established, and there are many routes, including online courses and on-the-job training.

Data science encompasses the theoretical and practical application of ideas, including Big Data, predictive analytics, and artificial intelligence.
Today, its importance to the world of business and commerce is well established, and there are many routes, including online courses and on-the-job training, that can equip us to apply these principles. This has led to democratization of data science, which we will impact many of the trends mentioned below, in 2022 and beyond.

1. Small Data and TinyML
The rapid growth in the amount of digital data that we are generating, collecting, and analyzing is often referred to as Big Data. It isn’t just the data that’s big, though — the ML algorithms we use to process it can be quite big, too. GPT-3, the largest and most complicated system capable of modelling human language, is made up of around 175 billion parameters.

2. Data-driven Customer Experience
This is about how businesses take our data and use it to provide us with increasingly worthwhile, valuable, or enjoyable experiences. This could mean cutting down friction and hassle in e-commerce, more user-friendly interfaces and front-ends in the software we use, or spending less time on hold and being transferred between different departments when we make a customer service contact.

3. Deepfakes, generative AI, and synthetic data
In 2022, we will see this trend bursting into many other industries and use cases. For example, it’s considered to have huge potential when it comes to creating synthetic data for the training of other machine learning algorithms. Synthetic faces of people who have never existed can be created to train facial recognition algorithms while avoiding the privacy concerns involved with using real people’s faces.

4. Convergence
AI, the internet of things (IoT), cloud computing, and superfast networks like 5G are the cornerstones of digital transformation, and data is the fuel they all burn to create results. All of these technologies exist separately, but combined; they enable each other to do much more.
In 2022, an increasing amount of exciting data science work will take place at the intersection of these transformative technologies, ensuring they augment each other and play nicely together.

5. AutoML
Short for “automated machine learning,” AutoML is an exciting trend that’s driving the “democratization” of data science mentioned in the introduction to this piece. Quite often, a large portion of a data scientist’s time will be taken up with data cleansing and preparation — tasks that require data skills and are often repetitive and mundane. AutoML at its most basic involves automating those tasks, but it increasingly also means building models and creating algorithms and neural networks. The aim is that very soon, anyone with a problem they need to solve, or an idea they want to test, will be able to apply machine learning through simple, user-friendly interfaces that keep the inner workings of ML out of sight, leaving them free to concentrate on their solutions.

For more such content, visit:



Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store


India's Largest Tech Community | 4.2 Million+ Developers | Guinness World Record Winner | Limca Book of Records