Business

Here’s why tech companies love data fabric

Data science has grown by leaps and bounds ever since its inclusion. It’s now almost become a necessity for all modern corporations to integrate a data management system within their plans. But, like with every other innovation, there’s always room for improvement and the conventional systems of data management are on the brink of becoming obsolete today. Given this background, one of the newer advancements that are making head turns and taking notice is a data fabric. So, what exactly is a data fabric and why are so many companies making the shift to integrate it within their existing technological infrastructure?

What is a data fabric?

A data fabric is an architectural framework that comprises a set of data services that is geared towards creating a unified platform for companies to better handle disparate sources of information. Seen as a successor to the conventional methods of data storage, a data fabric is an amalgamation of different data management technologies like data cataloging, data governance, and data integration.

The basic aim of data fabric is to provide the key stakeholders with the right information at the right time to allow them to make the best decisions for the business. Whether it be private or public clouds, IoT devices, or on-premises data sources, a data fabric is a one-stop solution for a company’s data storage needs. The dependency on towering data silos is eliminated and consistency is maintained across the platforms that are being serviced.

What are the capabilities that a data fabric addresses?

Now, that the question “What is data fabric?” has been sufficiently answered, the next step is to understand what are some of the key capabilities it addresses. Some of these capabilities that a data fabric focuses on include:

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1.      Data cataloging

As the name suggests, data cataloging refers to the process of maintaining a log of all the data assets and representing them visually for easy understanding.

2.      Data engineering

Data engineering is one of the most important components of a data fabric. It refers to the construction of robust and highly data pipelines that can handle large amounts of data with ease.

3.      Data governance

A data fabric architecture is expected to comply with a set of guidelines and privacy regulations set forth by standard organizations. The ability to adhere to such guidelines is referred to as data governance.

4.      Data orchestration

Data preparation and orchestration are at the heart of a data fabric. It comprises all the steps involved in transforming large data sets filled with numbers into insights about the business and the entire marketplace, as a whole.

Why are companies today shifting to data fabric?

A recent trend in the world of data sciences is the transitioning of companies from traditional forms of data management to more robust systems of data management like a data fabric. This can be justified based on the multiple advantages that a data fabric affords its users in comparison to other methods. Some of these advantages that merit a mention include:

A)    Unbiased decision making

Since the data collected is subjected to a series of analytical tools and is said to comply with the set privacy guidelines, businesses can be assured that the decisions that they’re taking will ultimately lead to the betterment of their companies. While the ultimate decision-making power rests in the hands of the owner with their intuition playing a major role, having hard facts as the basis for these decisions is a sure-fire way of eliminating bias and ensuring subjectivity.

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B)    Reduction in human error

With a data fabric, the entire process of collecting data from a variety of sources, collating them together, and drawing appropriate conclusions is automized. This step goes a long way in minimizing human error which is more or less inevitable when dealing with large volumes of information. Moreover, data scientists need not concern themselves with mundane tasks like constructing frequency charts and calculating averages. Freed from having to perform such tedious tasks, they are allowed to focus their time and resources in a sphere that may be of interest to the company.

C)    Better communication

One of the most underrated aspects of integrating a data fabric into a firm’s existing data infrastructure is that it ensures that all the different factions functioning within the company work well together. This is facilitated by the fact that all stakeholders who have a vested interest in the process of decision-making in the business share a common language. This also includes consumers who’re now on the receiving end of better customer service, all of which is attained at a fraction of the cost of the conventional systems of data management.

Conclusion

A data fabric has all the capabilities to be the next big thing in data management. It’s fairly easy to set up, works across multiple systems, is much safer, and addresses key capabilities like data cataloging, data engineering, data governance, and data orchestration. It also improves upon its predecessors by envisioning data as a product and by further optimizing the process of decision-making. Hence, a data fabric can be considered a viable option for businesses that are looking to provide a better customer experience at reduced costs.

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