Data Analytics Trends

Data drives an organization in many ways. More and more organizations are into data-driven models to streamline their processes. Organizations are leveraging the power of data analytics services to improve customer experience, optimize processes, and reduce costs.

Here are the main trends in Data Analytics to Look Out for in 2022

Data Fabric

Data fabric is an architectural framework; it includes data services to standardize data management practices across hybrid cloud environments. Data fabric reduces maintenance by 70% and design and deployment by 30%.

Cloud Computing

Cloud computation and hybrid cloud services are the hot data trends of 2022. Public clouds are not highly secure though cost-effective; private clouds are secure but very expensive. A hybrid cloud is a combination of private and public clouds, as a hybrid cloud is cost-effective and secure. Hybrid clouds offer scalability of data and offer a centralized database.

Augmented Analytics

Augmented Analytics is hugely popular; it utilizes Machine Learning, Artificial Intelligence, and NLP to enhance data analytics, insight discovery, and data sharing. Augmented analytics help in combining data inside and outside the organization.

Enhanced Consumer Experience

Customer experience is an integral part of any business. With data-driven customer experience, companies can leverage consumer data to enhance customer experience. Since every aspect of consumer interactions is becoming more digital (take examples of Amazon’s cashier-less convenience stores and AI chatbots), these interactions can be measured and analyzed to understand how the whole experience can be made more enjoyable.

Predictive Analysis

Predictive analysis leverages big data and business intelligence to forecast future trends. The process utilizes market data, and product performance data, along with cloud apps and social media. According to a report by Facts and Factors, by 2026, the Global Predictive Analytics market will reach USD 22.1 billion.

Self Service Analytics

This is the time that oversees a perfect mixture of technological and human intelligence. Self-service Business Intelligence (BI) tools help in extracting useful insights from business intelligence platforms. They generate real-time reports, which enable businesses to understand which areas to address. These tools play an important role in lowering operational costs. As per a report by Mordor Intelligence, the self-service business intelligence market will grow at a CAGR of 15.5% by 2026.

Mobile Data Analytics

Mobile data analytics offers enhanced components such as face ID, widgets, etc. It will be beneficial in closing business decisions faster. Other than that, apps of AR will help in viewing dashboards and datasets in interactive simulations. Therefore, it will be convenient to work on smaller screens.

Data for Agile Operations

Data needs to be usable; only then does it hold importance. Data is mostly collected from different channels, and it needs to be standardized. When the data is clean, it can be quickly accessed and holds meaning. Customer data platforms can unify data into an actionable profile. Since the needs of customers keep changing, profiles are refreshed in real-time.

Data Privacy

Public opinion towards data privacy has been shifting, given the fact that there have been many high-profile corporate data scandals in the past. Businesses first have to earn consumer trust for accessing their personal data. They need to be sure that the benefits of sharing their personal data are higher than any possible downsides. In addition to that, businesses need to be responsible for using the data effectively and be innovative in bringing customers new experiences to them in exchange for data.

Real-time Personalization

With data, businesses can understand customer preferences, and it provides them with a great opportunity to curate content with respect to user wants. Personalization is a great way of building a trusted relationship with customers, and for personalization, businesses need to understand the changing user needs. Businesses need to reach customers at just the right moments.


Automation includes various technologies to reduce human intervention in processes. It performs complex analysis quickly and efficiently. A huge amount of unstructured data analysis is automated to increase performance and efficiency.

Edge Computing

Though there are many big data analytic tools available, the problem of processing huge data still exists. A huge amount of data can be processed in a short time while offering better data privacy and security with quantum mechanics. Edge computing needs fine-tuning before it can be widely adopted by organizations. With time, it will become an imperative part of business processes.


XOps is an umbrella term that defines IT disciplines such as DevOps, DevSecOps, etc. AI and Data Analytics have made XOps crucial for any organization. Its goal is to improve business operations, increase efficiency, and enhance customer experience by delivering a flexible design by working hand-in-hand with other software disciplines.

Decision Intelligence

Decision intelligence has gained huge recognition in today’s market. With decision intelligence, organizations can gain insights needed to drive complex business decisions. AI and conventional analytics are also included in decision intelligence. Combined with a common data fabric, decision intelligence can greatly help organizations rethink the decision-making process. Engineered data intelligence is not to replace humans but instead to help in augmenting the decisions.

Final Words

Data is crucial for any organization, and seeing the importance of data, data analytics has grown in popularity with businesses. Data analytics and AI/ML services help organizations in making informed business decisions that help them in improving customer experience and efficiency and reducing costs. The trends listed above are popular in 2022, and the adoption of these trends can improve business operations greatly.

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