Do you know the terms data analysis, data science, and data engineering? Most certainly, you do. No one today is unfamiliar with the advances in this field of technology. The field of data science just keeps expanding at a fast pace. Even during the pandemic, when almost every other field witnessed a fall in growth, data science still maintained its ground. According to The State of Data Science, 26% of companies made more investments in data science, while 24% did not reduce their investment in this field. This field will garner more growth in the future. There is an increasing demand for data scientists, according to FutureLearn, so job opportunities in the field are increasing.
Trends in data science keep evolving. If you are a data scientist, you must probably be wondering how things will take a turn in 2022. Here we present to you seven trends that will prevail not only in 2022 but even in the coming years.
- Growth of Predictive Analysis:
Who doesn’t want to know what the future will be like and make decisions accordingly? Predictive analysis is the future of data science. Every company wants to know what optimal decision they should make to reach their goals. The predictive or forecasting analysis is the heart of data science. It refers to gaining insights from past and current data with the help of statistical tools. Which statistical tools, you might ask. Well, there are several tools for data analysis; for instance, organizations have been using SQL for data science activities for so long. The insights they get from the data serve as the basis for their strategies for the future.
- Cloud-Based AI and Data Solution:
There will be a tremendous shift towards cloud-based solutions in the coming years. There is already a huge amount of data; how to manage it is the question. The goal is to have one place where all data-related activities such as collecting, formatting, cleaning, labeling, arranging, and analysis can take place. A cloud-based platform can put all these things under one roof. The upcoming years will be very crucial for machine learning and data science industries as they will compete head-to-head with cloud computing behemoths in the war of budget, arms, and minds.
- Rise of Deepfake Audios and Videos:
This trend might scare you more than it excites you. But you cannot ignore it now that it’s gaining so much popularity. This might not be more of a positive trend in the future, but this will be influential for sure – bad influence or not – only time will decide. Deepfakes utilize artificial technology to fake someone else’s voice or face. Many frauds and thefts have taken place due to deepfakes. AI makes you think you are talking to someone by mimicking their voice and style. Deepfakes are also used to tarnish the reputations of big names in politics. The work on making technologies to tackle deepfake has begun, but until anything is official, you should keep an eye out for deepfakes. But hey, it’s not all bad. If used positively, it can help teach other machine learning algorithms by creating artificial data.
The term AutoML stands for automated machine learning, and yes, it’s as simple as its name. It means applying the techniques of machine learning models in real-world situations through automation. This will help get past the stage of manual coding. AutoML ‘automates’ the selection, parameterization, and construction of ML models. Automated machine learning can give accurate and quick results compared to manual or hand-coded methods. In coming years it is bound to gain popularity as it is easy to use and it is a data scientist’s great companion. It can perform repeated tasks easily so that the data scientist can have more time for more complex things.
- More Focus on Data Privacy:
One thing to know about the masses in 2022 is that everyone is aware of their right to privacy, and rightfully so. Recently, a lot of big companies were using and selling users’ private data without their consent. Now people care about cyber security more than ever. Not only on the consumers’ end, but data privacy is a concern for businesses and organizations too. Companies have to ensure their and their consumers’ data protection from any type of digital theft. In the coming years, proper data privacy laws are going to implement. Data privacy opts to give a safer approach for collecting and using consumers’ data.
- Powerful Conversational AI:
You must feel tired of hearing the world talking about artificial intelligence by now. But brace yourselves because AI is not going away any time soon, or even later. AI is the present and the future. There has already been so much development in AI, but particularly conversational AI will gain more importance in the coming years. Conversational means AI can converse with humans. AI uses language models to understand our languages and talk to us. Many tech giants have been putting forward different language models to enhance conversational AI. With the help of these models, human language is being transformed into computer codes for AI to understand. Computer codes are also turned into human languages for conversation. In the coming years, conversational AI will develop so much that you won’t be able to differentiate whether you are talking to a human or a machine.
- Augmented Consumer Interfaces:
Soon there might be an AI interface to assist you in shopping. In the future, you will buy things using virtual reality, while an augmented consumer interface will help you know more details and reviews of the product. It can be in the form of brain-computer interface (BCI) communication or AR on mobile. These are the technologies that have real-time effects on our shopping behaviors. The augmented consumer interface will soon take over zoom meetings. This might look like something from a science fiction novel, but it’s near reality. IoT, BCI, AR, VR, AI agents, and speakers; all these technologies will be game-changers in the face of augmented consumer interfaces. This will become a new paradigm where AI will be an intermediary.
The data industry is booming. Years of developments are happening in just a matter of months. The reason is that every industry depends on data science and data analysis. If you are a data scientist or a tech-savvy person, you must always try to keep up with ever-changing and ever-improving trends in data science.