The year 2021 was out of the ordinary as global businesses struggled to keep afloat amid the pandemic. This unusual situation accelerated digitization in businesses, which led to a surge in “digital data.”
This year witnessed a record number of hires of data scientist and data analyst positions as businesses realized that data-driven market intelligence was the primary driver of success in the digital business world. In a way, the pandemic brought about another technology revolution in the digital business world.
Due to the mass online migration of global businesses, 2021 witnessed the birth of many new Data Science trends in the data technology industry. Many of these trends started before 2021, such as cloud and scalable AI, graph analytics, or blockchain in analytics, and these will have additional impact in 2022. This DATAVERSITY® article discusses four Data Science trends that probably shaped 2021, two of which reappear here.
The available industry literature indicates a wide range of Data Science trends will dominate the 2022 business world, 11of which will be highlighted here.
Rise of Small Data and Scalable AI
The sudden surge of digital data and online professionals influenced a move away from big data, as data types and data usage became more diverse and more complex in the last two years. According to a Gartner Press release, 70% of organizations will shift their focus from big to small and wide data by 2025.
The prominent data analytics trend this year has been “small data,” with scalable artificial intelligence (AI) technologies to analyze customer behavior. Small data, though limited in volume, offers powerful insights. An important application of small data is self-supervised learning.
This key Data Science trend will continue through the coming years. Now let’s talk about the other trends that have already started or will start in the next few months:
10 Additional Data Science Trends Predicted for 2022
- Rise of Deepfake Technology: Deepfakes using AI is able to modify audio, image, or video files of one individual to impersonate another person. In 2019, podcaster Joe Rogan’s deepfaked voice went viral on social networks.
- Python Will Rule in 2022: In the application development market deep learning (DL) algorithms will rise in popularity, thus Python will gain prominence as the programming language of choice. Deep learning apps are slated to become the hot favorites of the global developers’ community in 2022.
- Explainable AI Platforms: AI-driven data analytics gathered steam when “explainability” became a huge issue for data processing teams. Business data must be understood by all business users, and this can only be achieved by sophisticated, rule-based logic. This explainable data-analytics trend is more visible in risk-oriented sectors like finance.
- Augmented Data Management: This growing trend will probably lead to an AI-human hybrid workforce, where AI- and machine learning-powered machines will work side by side with humans to improve and optimize work processes. All routine Data Management tasks will be completely automated to minimize human workloads. The “AI-human” hybrid teams, some think, may even lead to the formation of hybrid teams of programmers and developers. Is that thinking too far-fetched?
- More Awareness about Data Privacy: As data privacy laws like General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA) continue to be enforced across businesses, business users will have to become more alert to the sensitive nature of data collection, preparation, storage, and use in day-to-day business. Companies will have to be privacy-compliant in order to survive. These data privacy trends are predicted to have impact on global businesses between 2022 and 2025. Also on the rise: data protection by design.
- Growth of Decision Intelligence: The widespread popularity of Data Science, AI, and ML proves that major business operators such as Apple, Facebook, and Google enjoy technology-aided business decisions and even technology-guided competitive intelligence. In 2022, you may see a lot of big companies worldwide embracing “decision intelligence.” AI and ML techniques and tools will continue to provide deep insights for human decision-makers, with as much as 33% of organizations using them.
- Data Provenance: With the rising importance of metadata in Data Governance, data provenance, also known as data lineage — the holistic determination of the origin of a piece of data — has become a critical activity in all Data Science practices. This activity will gain traction in 2022. This overview guide explains why data lineage is important in the complex data analytics world of 2022.
- Customer Personalization: Online shopping became a popular trend during the pandemic, and offering new and novel customer experiences is a serious challenge for the retailers. All retail businesses have an online presence now. As the conversation in this Forbes post indicates, the retailers need “more than just the technology and budget — they require a culture of experimentation to design the kinds of experiences consumers expect.”
- Augmented Consumer Interfaces: Thanks to NLP technology, AI-powered consumer interfaces will operate more like human beings. Human consumer support agents use language for communication; similarly, NLP-enabled customer assistants, chat bots, and automated customer service platforms will start behaving more like humans through conversational interfaces. NLP will personalize the assisted consumer interfaces.
- Intelligent Feature Generation: With ML models becoming more critical for the success of smart devices, this trend will play a big role in all things AI in 2022. While this trend started this year, it will have long-term impact in the future years of data technologies.
Growth of Data Science Communities in South Asian Countries
The last trend that ought to be included in this post but not as a technology trend item above, is the huge growth of Data Science communities in Southeast Asia, especially China. The year 2022 will certainly witness a massive growth of the Data Science community, which includes data scientists, data analysts, data engineers, and data architects in China and other Southeast Asian countries.
Forbes author and industry insider Bernard Marr has listed the five DS Trends of 2022, while an InsideBigData article talks about ML trends to watch out for in 2022. Finally, if you wish to quickly compare the list of 2022 trends provided in this post vs the 2021 trends provided by Datacamp, check out this infographic.
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