Data Integration

Why Is Data Fabric Key to Emerging Technologies?

Data management agility is now highly critical for enterprises in this increasingly distributed, complex, and diverse environment. Therefore, business leaders must look beyond traditional data management practices and shift towards modern solutions like ‘data fabric.’ Data fabric is a robust solution to data management challenges. In this article at TDWI, James E. Powell and Jeff Fried discuss how data fabric fits into the landscape of emerging technologies—artificial intelligence and machine learning.

The Purpose of Data Fabric

Data fabric is relatively new, and many solutions are being offered under this name. However, only a few solutions can be considered as accurate data fabric technology. At a basic level, the technology helps organizations handle enterprise data in a better way. It does this by replacing copies with controlled access. Further, it offers a method for separating data from the applications that create it.

Data Fabric and Emerging Technologies

Data is a critical part of a successful digital transformation journey because it helps create new business propositions, enable new customer touchpoints, and optimize operations. Data fabric enables organizations to achieve these with its advanced integration and analytical capabilities. In other words, for organizations that aim to reap the benefits of emerging technologies, leveraging a data fabric will help them accelerate the ability to adopt AI and ML products.

Is It different from Data Storage Technologies?

“A data fabric is a reference architecture that provides the capabilities needed to discover, connect, integrate, transform, analyze, manage, utilize, and store data assets to enable the business to meet its myriad of business goals faster,” explains Fried. Additionally, data fabric is less complex than data lakes. An enterprise data fabric combines several data management technologies such as data integration, pipelining, API management, and others to provide new business insights.

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