Introduction
Big data has been at the forefront of discussions across industries in recent years, and rightly so. It has transformed business operations and provided companies with valuable insights to make informed decisions. The past year, in particular, has seen a surge in big data usage as organizations pivotted towards digital platforms due to the COVID-19 pandemic. As we move into 2021, there are a few predictions that the big data industry may expect. Here are five likely predictions for big data in 2021.
1. Importance of Edge Computing
Edge computing has been around for a while, but it is only gaining traction now. With the growth of the Internet of Things and the number of devices connected to the internet, the data generated has become overwhelming. Edge computing involves bringing the compute power closer to the source, such as sensors or IoT devices. This means that the data generated can be analyzed in real-time, leading to more accurate insights and reduced latency. In 2021, we can expect edge computing to play a vital role in big data analysis and storage.
2. Democratization of Data
Democratization of data refers to the process of making data accessible to everyone in an organization, regardless of their technical expertise. With the rise of data literacy and the availability of user-friendly tools, more people can now analyze complex data sets and gain insights. In 2021, we may expect organizations to continue making data accessible to a broader audience, enabling faster and more informed decision-making.
3. Greater Emphasis on Data Privacy and Security
As the use of big data continues to grow, the issue of data privacy and security is becoming more critical. With large-scale data breaches making headlines, organizations are under more pressure to secure their data. Customers are increasingly aware of the value of their data, and they expect companies to treat it with the utmost care. In 2021, we may expect stricter regulations and guidelines around data privacy and security, alongside increased efforts by companies to protect data.
4. Increased Automation
The use of automation in big data analysis has been around for some time, but it is only expected to increase in 2021. With the growing volume of data generated, automating processes such as data cleaning and analysis can speed up the process and reduce errors. Moreover, Machine Learning algorithms can analyze data over multiple gauges, providing the opportunity to make better predictions and identify growth opportunities.
5. Convergence of Big Data and AI
Artificial Intelligence (AI) is all about making machines learn and make decisions based on data. Thus, the convergence of AI and big data makes sense, with the potential of both technologies when combined. With AI, big data sets can be searched more comprehensively, leading to smart and informed decisions at a quicker pace. AI also enables data scientists and businesses to develop insights beyond statistical modeling by detecting patterns, highlight specific behaviours, etc.
Conclusion
2021 is expected to bring many opportunities for the big data industry. The relentless growth of big data applications has already initiated a revolution in the modern technological world, and we are likely to witness several innovations and advancements in the upcoming years. From increased emphasis on edge computing, effective democratization of data, stricter data privacy and security measures, to increased automation and the convergence of big data and AI, the future of big data looks promising. As we continue to adhere to professional language usage, these five predictions can serve as a valuable guide to organizations looking to stay ahead of the curve in 2021 and beyond.
