Today’s organizations are being driven by data in countless ways. Big Data Analytics, Data Science and Artificial Intelligence are key trends in the accelerating market. As more companies adopt data-driven models to streamline their business processes, the data analytics industry is seeing huge growth. From fueling fact-based decision-making to adopting data-driven models to expanding data-focused product offerings, organizations are inclining more toward data analytics.

These data analytics trends can help you deal with many changes and uncertainties. Let's take a look at a few of these trends that are becoming an inherent part of the industry.

Artificial intelligence is getting smarter and more powerful every day.

COVID-19 has changed the business landscape in myriad ways. For example, historical data is no longer relevant, so COVID-19 systems are now being used to analyze small data sets. These systems are highly adaptive and can work with small data sets. They protect privacy, are much faster than traditional AI techniques, and also provide a faster return on investment. The combination of AI and Big data can automate and reduce most of the manual tasks.

Agile and Composed Data & Analytics

Data & analytics models are capable of digital innovation, differentiation, and growth. Agility at the edge and composability in data analytics can help you provide a user-friendly, flexible, and smooth experience using multiple data analytics, Artificial Intelligence (AI), and Machine Learning (ML) solutions. This will not only enable you to connect business insights and actions but also encourage collaboration, promote productivity, agility and evolve the analytics capabilities of your organization.

Hybrid Cloud Solutions and Cloud Computing

One of the biggest data trends for 2022 is the increase in the use of hybrid cloud services and cloud computing. Hybrid clouds offer a balance between public and private clouds by providing high security along with cheap cost. This is achieved by using artificial intelligence and machine learning. Hybrid clouds are bringing change to organizations by offering a centralized database, data security, scalability of data, and much more at such a cheaper cost.

Data fabric

 A data fabric is a framework that standardizes the way data is managed across hybrid multi-cloud environments. It reduces design, deployment, and maintenance time by 30%, 30%, and 70% respectively, thereby reducing the complexity of the whole system. Since it's a re-architect solution as an IaaS platform, it will be highly adopted by 2026.

Edge Computing For Faster Analysis

There are many big data analytic tools available in the market but still persists the problems of enormous data processing capabilities. This has led to the development of the concept of quantum computing. By applying laws of quantum mechanics, computation has speeded up the processing capabilities of the enormous amount of data by using less bandwidth while also offering better security and data privacy. This is much better than classical computing as the decisions here are taken using quantum bits of a processor called Sycamore, which can solve a problem in just 200 seconds.

Augmented Analytics

Augmented Analytics is another leading business analytics trend in today’s corporate world. This is a concept of data analytics that uses Natural Language Processing, Machine Learning, and Artificial Intelligence to automate and enhance the work of data scientists. It helps them integrate data from within the enterprise and outside the enterprise and derive insights from it.

The Death of Predefined Dashboards  

 Earlier, dashboards were only present in predefined static formats. But now they have become outdated due to the lack of interactivity and user friendliness. There have been questions raised about their utility and ROI, leading organizations and business users to look for solutions that will enable them to explore data on their own and reduce maintenance costs.

XOps

 XOps has become an integral part of business transformation processes, with the adoption of Artificial Intelligence and Data Analytics across any organization. XOps started with DevOps—the combination of development and operations—and its goal is to improve business operations, efficiencies, and customer experiences by using the best practices of DevOps. It aims in ensuring reliability, re-usability, and repeatability; ultimately enabling economies of scale and helping organizations to drive business values by delivering a flexible design and agile orchestration in affiliation with other software disciplines.

Engineered Decision Intelligence

Decision intelligence is gaining a lot of attention in today's market. It includes a wide range of decision-making and enables organizations to more quickly gain insights needed to drive actions for the business. It also includes conventional analytics, AI, and complex adaptive system applications. When combined with composability and common data fabric, engineered decision analytics has great potential to help organizations rethink how they optimize decision-making. In other words, it's not made to replace humans but rather augment their decisions making power.

Data Visualization

The data visualization market has grown with the evolution of business intelligence. Visualization is the last stage of the analytics process and allows enterprises to perceive vast amounts of complex data. Data visualization helps companies make decisions more easily by using interactive visual ways. It influences the methodology of analysts by allowing them to observe and present data in patterns, charts, graphs, etc. Since the human brain interprets visuals more quickly, it is a great way to predict future trends for your firm.