Top Data Fabric Trends for Enterprises in 2022 and Beyond

This year we should see lots of action in data fabric adoption and upgrades as the architecture proves useful for many use cases.

Yash Mehta

May 10, 2022

6 Min Read
Top Data Fabric Trends for Enterprises in 2022 and Beyond
(Source: Pixabay)

Last year was a defining year for many technologies, including data fabrics. It provided the much-needed ground to prove its worth amidst rising concerns about the existing data management practices. As per Expersight, the industry is moving in the right direction, with Data Fabric’s market value to touch USD 4.2 bn by 2026.

A data fabric is simply an architecture that gives us the visibility of data and the ability to move it wherever we want. It also allows you to replicate data and access it across cloud resources and hybrid storage. This year should witness a lot of action in terms of upgrades and adoption.

Addressing integration complexities

Because integration plays a big role, organizations are investing in data platforms that will eventually allow for resilient and flexible data integration across a variety of business users and infrastructure hosting solutions. They want to create a scalable architecture that can help overcome several roadblocks caused by the rising data integration challenges in the industry.

Let’s look at an example of IBM to understand this better. They offer different integration tools that can be deployed in both in-situ and cloud environments virtually for every enterprise use case. The on-premises data integration suite is equipped with featured tools for both traditional and modern integration requirements. These range from replicating and batch processing data to its synchronization and visualization. In addition to this, IBM also offers several other pre-built connectors and functions. They also roll out additional functionalities on a perpetual basis. So, no doubt, their cloud integration product is one of the best in the market today.

Micro-DB for data fabrics

This type of data fabric allows you to organize any fragmented data from a source system/s following the business entity. It can be anything from a customer, location, product, or order to any other parameter that is of significance to the business. The data for every individual is stored in a unique Micro-Database and brings together everything that the company learns about the entity. It can be interactions, transactions, or even master data. There couldn’t be a better case study than K2View to understand this.

The data fabric not only integrates, transforms, and orchestrates data but also enriches and secures it into Micro-databases in real-time. These Micro-databases can either be accessed with a web service or can be channeled to analytical data stores. Their data product platform allows you to create a common business language for your company’s data irrespective of any underlying technologies, source systems, or data formats. This helps data consumers get easy and instant access to secure data. This fabric is scalable and can support millions of micro databases persisted, concurrent, or virtualized in a distributed, high-performing architecture. It can also update data into the source systems with ease.

Hyper automation that favors human intelligence

Companies nowadays face challenges like the acceleration of time-to-market along with the necessity to go back to rapid and solid economic growth. This is why these companies look for integration solutions that minimize and limit human intervention. Today, the challenge we face is to win against the ticking clock and divert human intelligence to real tasks that add value.

Gartner states that hyper-automation will be one of the key trends in the coming year. This will allow for massive use of advanced technologies like machine learning and AI to augment human capabilities and automate processes at the same time. Gartner states clearly in its report, “The most successful hyper-automation teams focus on two key priorities that include improving the overall quality of work, increasing decision-making agility, and accelerating businesses.

Cloud-native platforms: Adaptability, profitability & scalability

The next most important data trend is the unavoidable place that could-native platforms hold in the data environment. These platforms respond well in terms of both cost control and performance because they promise adaptability and scalability.

These cloud-native platforms exploit the fundamental capabilities of cloud computing. They do so to be able to provide elastic and scalable IT capabilities as a service. Such platforms are expected to be the foundation of 95% of digital transformation projects of companies by 2025 as compared to the previously estimated 40% by 2021.

Hybrid clouds

With the advent of time, the use of unstructured file data has grown by leaps and bounds. This also means that the cloud is now being used as a secondary or even tertiary storage tier. For organizations that use different clouds for various data sets and use cases, multi-cloud strategies are known to work the best. But this also gives birth to another issue that companies cannot often ignore.

Moving data from one cloud to another can be quite expensive in case you wish to do so at a later stage. A new strategy is to pull the computer towards data that is in the same location. This central location can serve as a hub or collocation center giving out direct links to cloud providers. In the meantime, the multi-cloud scenario will evolve with several strategies that allow the computer to access your data or may even let the data reside in several locations.

Storage-agnostic data management: A critical component of modern data

Thanks to near real-time analytics, data owners can now control where their data will live across storage and cloud. This helps them place data in the right place at the right time. IT managers and storage professionals will plump for data mesh architectures that will allow them to enable data-centric instead of storage-centric management and also help in unlocking data from storage.

For example, storage pros earlier used to store all medical images on the same NAS. Now they can easily use user feedback and analytics to segment these files. They can do so by copying medical images to give access to machine learning in any clinical study. They can also move critical data to immutable cloud storage if they need to combat ransomware.


2022 is an important year largely because it could be our recovery from the infamous pandemic. There’s a lot of responsibility to the matchup for the backlogs by fastening data throughput and business processes. Thus, fabric adoption will play a key role in achieving the mission across sectors.

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About the Author(s)

Yash Mehta

Yash Mehta is an internationally recognized IoT, M2M, and Big Data technology expert. He has written a number of widely acknowledged articles on Data Science, IoT, Business Innovation, and Cognitive intelligence. His articles have been featured in the most authoritative publications and awarded as one of the most innovative and influential works in the connected technology industry by the IBM and Cisco IoT departments.

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