Data Management 2022: Trends that Will Define the Year

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For decades, organizations have managed their data only by collecting, analyzing and storing it. However, in recent years businesses have realized the importance of data and are looking for ways to extract critical information from this data. Massive amounts of data are generated daily and stored in various locations. This data is accessed from corporate data centres to the cloud and the edge.

Modern technologies such as Artificial Intelligence (AI) and Machine Learning (ML) have facilitated the field of data analytics and now have become the must-have capability in 2022. The future will only amplify the importance of these technologies. Today enterprises need to rapidly sort through the unstructured data to find information that can effectively drive business decisions.

Below are a few trends that will be at the fore of data management in 2022.

Focus On Unstructured Data Analytics
Earlier, the focus of data science was only to feed structured data to the data warehouse. However, recent studies found that around 90% of the world’s data is unstructured. Additionally, with the robust rise of the use of machine learning that relies on unstructured data, data companies should invest in enhancing their skills to incorporate unstructured data analytics.

Businesses need to find efficient and effective ways to draw out value from the data that has no specific structure and outline. The data could range from genomic files, video files, seismic images, audio recordings, IoT data and user data such as emails. Developing skills that will help companies stay competitive, help experiment with new unstructured data and help learn unstructured data management techniques will be paramount in 2022.

‘Right Data’ Analytics Will Overshadow Big Data Analytics
As the name suggests, Big Data, in reality, is too big to handle. It has resulted in the creation of data swamps which is quite difficult to leverage. Finding the precise data in place, regardless of its point of origin and then using that data for data analytics is a game-changer. Finding the right data will save ample time and manual efforts while supplying more relevant analysis. So instead of big data, the new trend that would take its place will be so-called “right data” analytics.

Use of Storage-agnostic Data Management in Modern Data Fabric
Data fabric is a type of architecture that provides visibility of data. Not only that, but it also gives you the ability to access, replicate and move data across cloud resources and hybrid storage. With the advancements of real-time analytics, data owners can now control where their data lives across storage and cloud. This will allow data owners to put their data in the right place at the right time. Now storage and IT managers can choose data fabric architecture to unlock data from storage and enable storage-centric vs. data-centric management. For example, for a clinic, instead of storing all the medical images on the same NAS, storage experts can segregate these files using analytics and user feedback. Segregation can be done by copying medical images so that they can be accessed by ML in a clinical study. Or, moving important data to immutable cloud storage to protect it from ransomware.

Data Fabrics Will Be A Key Strategy
Data fabric recognizes all the places that your data is living and can bridge the gaps. It can help businesses in delivering greater visibility, portability and governance. Earlier research on data fabric was focused on structured and semi-structured data. However, as we know 90% of the world’s data is now unstructured. For example, X-rays, videos, log files, genomic files, sensor data etc. are data without a defined schema. It is difficult for data lakes and data analytics applications to access this data which are locked in files. Data fabric technology needs to connect the unstructured data storage (object and file storage) and data analytics platforms (including machine learning, natural language processors, data lakes and image analytics). It is becoming crucial to analyse unstructured data as machine learning also relies on unstructured data. Data fabric technology needs to be standards-based and hopefully open-source so as to reap the full benefits.

Data fabric technology is most likely to move from being a vision to a set of architectural principles of the field of data management. It is advisable for technology vendors to incorporate unstructured data into their data fabric architectures, keeping in mind the magnitude and the rising relevance of this technology.

Multi-cloud Infused With Data Strategies
Today various organizations have a hybrid cloud environment in place. It stores bulks of data and is backed up in a private data centre spread across various vendor systems. As unstructured data grows at an exponential rate, the use of the cloud as a secondary or tertiary storage tier has also increased. Also, it can be difficult at times to reduce cost, ensure performance and manage risks. As a result, businesses have realized that extracting value from data across on-premises environments and the cloud is a daunting challenge.

Some organizations incorporate multi-cloud strategies as they use different clouds for different data sets and use cases. This brings me to another point: that moving data is quite expensive from one cloud to another. A newer concept is to access data right where it is stored. This place could be a colocation centre with direct links to their respective cloud providers. It is for sure that Multi-cloud will evolve with different strategies in 2022.

Synthetic Data + Unstructured Data
Data privacy and security is becoming a major concern for businesses today. Synthetic data can be an immaculate solution to prevent user data collection. Synthetic data is also profitable for businesses as there aren’t many privacy laws to consider. Even when synthetic data lessens the customer data footprint, it still is a small part of the total unstructured data. The maximum amount of data is application-generated and not user data. If unstructured data is coupled with unstructured data management, it can help in managing data growth.

Today enterprises are still under a considerable amount of pressure regarding the adoption of data management strategies. Businesses are hoping to find useful information from the huge data deposit to drive critical business decisions. Analytics will always be an integral part of this effort as will creating standards-based data fabrics that can enable organizations to control data for action and analysis.

These were a few trends that would be visible in 2022. However, only the future will tell what trends will prevail and which will not. If you are looking out for data management services, book a free call with our experts.

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