Latest Big Data and Analytics Trends to Consider in 2021

by February 23, 2021

Big Data and Analytics

How are big data and analytics solutions revolutionizing businesses in the digital age?

Technology is relentlessly evolving with pace. Whether it is self-driving cars, robots or heavy autonomous machines, technology is only becoming better with time. However, all of these technologies rely heavily on data, the new oil for businesses of all sizes and types, and advanced analytics technologies that interpret that data. As big data plays a crucial role in driving organizations’ digital transformation, data analytics allows leaders to construe their data and derive meaningful insights from it. Big data analytics gives businesses the ability to make data-driven decisions that can improve business-related outcomes.

With the rapid surge in its adoption, the big data analytics market is forecast to reach US$274.3 billion by 2022, at a CAGR of 13.2 percent during the period of 2018-2022.

Let’s have a look at the top big data and analytics trends that will dominate in 2021 and beyond.

 

Decision Intelligence

Decision intelligence defines as a trending field that involves various decision-making methods to design, model, align, deploy and track decision models and processes. It also contains a framework that coalesces traditional techniques like rules-based approaches with advanced techniques such as AI and machine learning. It is expected that many organizations will have analysts practicing decision intelligence including decision modeling in the future.

 

X Analytics

Coined by Gartner, X analytics is an umbrella term in data analytics. As this new concept is primed to gain traction in coming years, X is the data variable for a range of different structured and unstructured content such as text analytics, video analytics, audio analytics, etc. X analytics will be used by data and analytics leaders to solve challenges in society, including climate change, disease prevention and wildlife protection.

 

DataOps

DataOps refers to an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data scientists to provide the tools, processes and organizational structures to support the data-driven enterprise. DataOps teams value analytics that work, measuring the performance of data analytics by the insights they deliver. They also embrace change and always look for constantly understanding evolving customer needs.

 

Augmented Analytics

Data is everywhere now and more of it is being produced every minute. The use of augmented analytics can enhance data analysis by creating, developing and sharing data analytics using AI and ML. It creates more efficiency in the data analysis process, provides businesses the tools that can answer their data-based questions in a matter of time, and assists them in staying ahead of the competition.

 

Hybrid Cloud

Cloud computing has a great impact on big data analytics as it stores vast data sets and acts on real-time information. Today, many big data and analytics use cases are running on hybrid cloud infrastructure. As an IT architecture, a hybrid cloud combines on-premises and local cloud resources integrated with one or more dedicated clouds, allowing for enhanced scalability and computational power for big data and analytics capabilities.

 

Data Stories 

Data stories are becoming a more popular way of conveying business information and driving outcomes. Companies nowadays can glean data on every aspect. Despite this, they still are unable to fully capitalize on opportunities concealed in their data. Storytelling was a key for the knowledge transmission across large groups of people. And in today’s data-powered world, it is becoming inevitable. Indeed, Gartner predicts that data stories will become the most popular method of conveying data insights by 2025.

 

Converged Analytics

IT specialists and data analysts are the only ones who use analytics until now, to create data visualizations that support the decision-making process. However, with today’s notion of self-service, these tools are more broadly used by different roles in the enterprise. According to Gartner, non-analytic applications will evolve to integrate analytics over the next few years. It is also expected that 95% of Fortune 500 companies will have converged analytics governance into broader data and analytics governance initiatives by 2023.

 

The Wrap Up

New trends in big data and analytics will continue to evolve. Companies need to stay focused and updated with relentlessly growing trends to drive successful digital transformation. They must understand how they can harness data analytics that allows them to understand their market better and enable them to stay ahead of their competitors.