Top 10 Data Analytics Trends For 2022
In today’s current market trend, data is driving any organization in a countless number of ways. Data Science, Big Data Analytics, and Artificial Intelligence are the key trends in today’s accelerating market. As more organizations are adopting data-driven models to streamline their business processes, the data analytics industry is seeing humongous growth. From fueling fact-based decision-making to adopting data-driven models to expanding data-focused product offerings, organizations are inclining more towards data analytics.
These progressing data analytics trends can help organizations deal with many changes and uncertainties. So, let’s take a look at a few of these Data Analytics trends that are becoming an inherent part of the industry.
Trend 1: Smarter and Scalable Artificial Intelligence
COVID-19 has changed the business landscape in myriad ways and historical data is no more relevant. So, in place of traditional AI techniques, arriving in the market are some scalable and smarter Artificial Intelligence and Machine Learning techniques that can work with small data sets. These systems are highly adaptive, protect privacy, are much faster, and also provide a faster return on investment. The combination of AI and Big data can automate and reduce most of the manual tasks.
Trend 2: Agile and Composed Data & Analytics
Agile data and analytics models are capable of digital innovation, differentiation, and growth. The goal of edge and composable data analytics is to provide a user-friendly, flexible, and smooth experience using multiple data analytics, AI, and ML solutions. This will not only enable leaders to connect business insights and actions but also, encourage collaboration, promote productivity, agility and evolve the analytics capabilities of the organization.
Trend 3: 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 computation. Public clouds are cost-effective but do not provide high security whereas a private cloud is secure but more expensive. Hence, a hybrid cloud is a balance of both a public cloud and a private cloud where cost and security are balanced to offer more agility. 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.
Trend 4: Data Fabric
A data fabric is a powerful architectural framework and set of data services that standardize data management practices and consistent capabilities across hybrid multi-cloud environments. With the current accelerating business trend as data becomes more complex, more organizations will rely on this framework since this technology can reuse and combine different integration styles, data hub skills, and technologies. It also reduces design, deployment, and maintenance time by 30%, 30%, and 70%, respectively, thereby reducing the complexity of the whole system. By 2026, it will be highly adopted as a re-architect solution in the form of an IaaS (Infrastructure as a Service) platform.
Trend 5: 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.
However, Edge Computing will need a lot of fine-tuning before it can be significantly adopted by organizations. Nevertheless, with the accelerating market trend, it will soon make its presence felt and will become an integral part of business processes.
Trend 6: 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 data analytics, data sharing, business intelligence, and insight discovery.
From assisting with data preparation to automating and processing data and deriving insights from it, Augmented Analytics is now doing the work of a Data Scientist. Data within the enterprise and outside the enterprise can also be combined with the help of augmented analytics and it makes the business processes relatively easier.
Trend 7: The Death of Predefined Dashboards
Earlier businesses were restricted to predefined static dashboards and manual data exploration restricted to data analysts or citizen data scientists. But it seems dashboards have outlived their utility due to the lack of their interactivity and user-friendliness. Questions are being raised about the utility and ROI of dashboards, leading organizations and business users to look for solutions that will enable them to explore data on their own and reduce maintenance costs.
It seems slowly business will be replaced by modern automated and dynamic BI tools that will present insights customized according to a user’s needs and delivered to their point of consumption.
Trend 8: XOps
XOps has become a crucial part of business transformation processes with the adoption of Artificial Intelligence and Data Analytics across any organization. XOps started with DevOps that is a 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 and also ensure a reduction in the duplication of technology and processes. Overall, the primary aim of XOps is to enable economies of scale and help organizations to drive business values by delivering a flexible design and agile orchestration in affiliation with other software disciplines.
Trend 9: 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, engineering decision intelligence has great potential to help organizations rethink how they optimize decision-making. In other words, engineered decision analytics is not made to replace humans, rather it can help to augment decisions taken by humans.
Trend 10: Data Visualization
With evolving market trends and business intelligence, data visualization has captured the market in a go. Data Visualization is indicated as the last mile of the analytics process and assists enterprises to perceive vast chunks of complex data. Data Visualization has made it easier for companies to make decisions by using visually interactive ways. It influences the methodology of analysts by allowing data to be observed and presented in the form of patterns, charts, graphs, etc. Since the human brain interprets and remembers visuals more, hence it is a great way to predict future trends for the firm.
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