In a fast-moving world as we are living in today, every day there is a new technology which changes the way we work, makes our existing systems redundant or needs patches and fixes to protect our costs.
One such technology that is expected to make our Big Data experience better and help businesses leverage it much better is Data Fabric.
Gartner identifies Data Fabric as one of the 10 new trends related to data management that will gain prominence in the coming years. Data Fabric refers to a single and consistent data management framework that enables smooth access and sharing of data in a distributed data environment.
Gartner also predicts that by 2022, businesses will opt for customized data fabric designs as a static infrastructure that will replace more dynamic data mesh approaches.
A Marketsandmarkets.com report predicts the data fabric market will grow at a Compound Annual Growth Rate (CAGR) of 26.6% from USD 653.5 million to USD 2,125.1 million between 2017 and 2022.
This corresponds to Forrester’s prediction that insights-driven businesses will grow at a rate of 30% to earn $1.8 trillion by 2021. Data fabric is becoming essential to derive those insights from the ever-growing volume of data that needs an agile and reliable data fabric.
Today, it is a given that businesses have access to large volumes of a variety of data which can help with informed decision making and improving efficiencies.
However, the data is heterogeneous, including not just numbers but also text, images, video and audio. It is available in structured and unstructured formats.
Businesses also have moved away from pure on-premise or on-cloud environments to embrace hybrid environments and this makes it difficult to manage and leverage data stored in database management systems deployed across different platforms.
Over time, these DMS tend to become siloed and therefore incapable of providing an enterprise-wide view.
What businesses need today is a combination of architecture and technology that can make managing the data simpler.
A bespoke, unified architecture with services or technologies running on it acts as the fabric weaving in different locations, types and sources of data using pre-built connectors and components.
Access to reusable data services, pipelines, semantic tiers or APIs is made simpler by the use of multiple data integration approaches in a synchronized manner.
Data fabric also makes processing, managing, and storing data easier. A data fabric is not dynamic and its value lies in the reusability of data to suit different needs across locations.
For instance, AI/ML processes can augment the capabilities of the data engineer to identify and address the challenges of data refactoring, modeling, production of schema and data quality recognition.
A data scientist can create expanding data related alerts relevant to the project being worked on. Data modelers, administrators and integrators can focus on verification more than data modeling. Information architects can identify how the data asset can be used and imputing it as metadata.
Businesses ready to leverage Big Data to improve their decision-making capabilities as well as customer engagement and operational efficiencies can benefit from the implementation of a data fabric strategy in many ways:
Data fabric can be used in any business that deals with data – and that cuts across segments. From banking, finance, healthcare, e-commerce to manufacturing, every industry today needs data insights for all their operations and functions.
The Marketsandmarkets.com report identifies three critical areas where data fabric can be of relevance though this is not restricted to these:
The volume, variety and velocity of data make security management difficult for businesses and preventing fraud is a top priority.
Data fabric automates the detection of data anomalies automatically and triggers actions to counter it. This not only minimizes losses but also improves regulatory compliance.
By ensuring data veracity and integration, data fabric provides the sales and marketing teams with data extracted from embedded devices, web logs and other such sources providing deeper insights into customer behaviors and preferences. This can help devise strategies with greater RoI and outcomes.
With regulatory requirements for data governance and risk management becoming stringent, compliance management has become a critical task for businesses.
Data fabric enables defining the guidelines and controls for the organizational governance process, improving an enterprise’s risk management capabilities and monitoring it through operational dashboards and risk scorecards.
By reducing non-compliance, it also improves cost-savings on potential penalties with the regulatory authorities as well as protects brand reputation.
For all its benefits, it is important to have the right implementation strategy for a data fabric to deliver as expected.
It requires an understanding of data, databases, data management systems, cloud and on-premise technologies such as SQL, NoSQL, Hadoop, AWS, and so on. It needs IT capabilities and supporting infrastructure.
For user industries, this can prove to be a drain of resources. Working with an outsourced partner such as Indium Software, a two-decade-old software solutions provider, businesses can benefit from their expertise and experience in having a future-ready, scalable and flexible implementation.
Indium Software has been working with cutting-edge technologies and has a team of Big Data experts with experience across different industries, in hybrid environments and with data management.
The domain knowledge with technological capabilities enables the Indium team to understand client requirements and create the data fabric suited to their needs.
If you would like to know how data fabric can help you improve your growth curve, contact us now.
By Uma Raj
By Uma Raj
By Abishek Balakumar