Top 10 Data Analytics Trends to Watch in 2022
It is becoming more and more apparent how data analytics is driving e-commerce revenues. And this growing importance has forced e-tailers and e-commerce firms to hire more data scientists in order to better understand how customer engagement impacts revenue and sales.
As we go about our daily lives, we are generating ever growing amounts of data. If you are a small business owner or a business manager, you need to know about the latest data analytics trends that can impact you. Some of these trends have been around for a while, but in 2022, we expect to see them begin to have a greater impact with the development of many more real-life applications.
Here are the 10 ways data analytics will storm the stage in 2022:
1. Engineering and DevOps teams will need to manage performance like a product, using data from monitoring solutions and advanced analytics to shift from firefighting to most recent issues or optimizing the slowest pages to identifying the key areas that need attention.
2. Data scientists will become social “glue” that will compel business and technology teams to work in close collaboration, because data teams will continue to discover strong correlations between business metrics and technical metrics.
3. Machine learning will evolve beyond theory into a business reality. ML problem alerts will carry context created through Big Data insights that support quick diagnosis and remediation.
4. New technologies, including stream processing and data integration in the stream, will emerge.
5. Data analytics will serve as a beacon for organizations to sail into uncharted waters. Source
6. Cybersecurity Analytics, Blockchain, and Privacy-Enhancing Computation
Cybersecurity strategies that protect traditional perimeters: processing, sharing, transferring, and analyzing are becoming more prevalent among businesses. This proactive approach to cybersecurity is identity-based and uses data collection and analytics (Cybersecurity Analytics) capabilities for faster threat detection and manual security tasks.
7. AutoML – Automated machine learning (AutoML) is an exciting trend that refers to the process of automating the tasks of applying machine learning to real world problems.
AutoML tools try to make machine learning accessible for non-machine learning experts. The goal is to allow anyone to apply machine learning through simple, easy to use interfaces to automate data cleansing and preparation. In the long-term, AutoML will also help in building models and creating algorithms and neural networks.
8. Quantum AI Gains Momentum
More and more companies are investing in Quantum AI because they expect it to become the next revolution. We are currently experiencing significant parallelism in how quantum computing develops and its convergence with advanced analytics techniques. We must make conscious and consistent use of this new paradigm’s benefits.
9. Metaverse Ecosystem: Enabling Extended Reality
Metaverse is not just a buzzword in the technology sector; it’s an ecosystem that will facilitate the exploitation of the so-called EX, i.e., extended reality. Under the EX umbrella, we find all immersive technologies that merge the real world with the virtual one: augmented, virtual and mixed reality.
10. Generative AI: A Leap Forward to Auto-generated Content
Artificial Intelligence is usually used to train algorithms based on conclusions, but can it create content and innovate on its own? The answer is yes, and it lies in Generative AI, one of the most promising developments in the AI environment in the coming years. Generative AI allows computers to automatically recognize underlying patterns related to input information and then generate new original content.