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7 Reasons You Need to Consider Data Fabric Now
Data fabric is among the terms more recently added to the glossary of data terms by industry experts. Since 2021, Gartner has listed data fabric as one of the most important trends in data solutions, yet the adoption rate of data fabric-based solutions remains low. In this blog, we will discuss 7 reasons why your organization needs to consider data fabric nowFirst, let’s understand what data fabric is.
What is Data Fabric?
Data fabric is an architectural approach that uses metadata, machine learning, and automation to weave together data of any format in any location and make it easy to find and use by people or systems. It unifies the separate functions of data management—integration, preparation, cataloging, security, and discovery—into a cohesive process through intelligent automation. To learn more about data fabric, here is a recent Eckerson white paper Data Fabric: The Next Step in the Evolution of Data Architectures.
Data-driven Digital Transformation
To develop new and existing opportunities and stay ahead of competition, organizations are looking to utilize data-driven digital transformation. Digital transformation improves knowledge, streamlines processes, increases integration, and leverages both online and offline data. According to a survey of boards of directors done by Gartner, nearly 70% of organizations have accelerated their digital transformation plans.
Whether you have already started your data-driven digital transformation or are in the planning process, a data fabric architecture can accelerate your journey. A data fabric provides meta intelligence that enables you to know what data is available, allowing you to create a data foundation that spurs innovation while maintaining customer trust. Using data fabric as a basis for a data-driven digital transformation saves time, money, and specialized work while building a flexible and scalable base for your future data solution.
Promote Data Democratization
Organizations understand the value of improving business performance by gaining insights from data, creating a need for non-technical people to be able to make sense of data. As a result, organizations have a pent-up demand for data democratization.
The democratization of data is possible when business users have the required level of data literacy to produce the needed insights or reports. However, this can’t happen without the right infrastructure. Data fabric provides the required infrastructure, minimizing reliance on tech teams.
Data fabric helps organizations become more self-sufficient because it provides guidance and consistency for all applications and hides the complexities of enterprise data. With data fabric, end consumers don’t have to know where or in what format data is stored. Hence, by increasing access and decreasing the need for in-depth, technical knowledge, data fabric is democratizing data.
Better Decision Making
To make the right business decisions, organizations need to ensure that their users have access to high-quality, trusted information.
Data Fabric helps manage catalog more intelligently. It enables users to create, view, and manage metadata. Cataloging helps capture how data is used, such as how often tables are accessed, in which queries they appear, and who is using them, allowing data consumers to not only gain quality data but also trust that data. Furthermore, cataloging helps data producers understand how data is being used in business contexts and what data is mission-critical.
Unified Data Governance and Compliance
Data governance and compliance have become more critical due to industry standards and policies along with newer data privacy rules and mandates. Organizations need data governance and compliance to protect their data from misuse.
Through automation, data fabric allows you to add an active governance layer, reducing your compliance and regulatory risks by applying automatic policy protection and compliance. When governance and security are applied consistently throughout the data process, data is checked at multiple stages and automatically monitored for potential problems. As the data fabric architecture includes various points of access for data, obtaining a holistic overview is essential to retaining audit trails and ensuring security without blocking data access from users who need it.
For more on the evolution of data analytics and governance platforms, check out this blog article on Flexibility vs Security in Data Governance.
Improve Data Agility
Organizations have realized that they need to think beyond static data. In a Forrester Analytics survey, data and analytics leaders articulated the need for real-time data as a top requirement. However, traditional data architectures were not designed to meet data arriving at different velocities. In most cases, organizations have to rely on a batch process, which slows the development of insights.
A data fabric architecture allows users to have a holistic view of their data, regardless of the data’s velocity. It provides a unified data operations layer spanning a wide range of sources to support any use case at any speed. With real-time data, insights are delivered as they happen. This streamlines processes, allows monitoring for future problems, and provides the basis for better decision-making across the board, increasing your ability to gain insights efficiently.
Eliminate Data Silos
Data silos are a natural consequence of growth and complexity. This is a result of organizations storing their data spread in numerous files, databases, and data warehouses that may span multiple clouds and on-premise systems. Silos can also be created by transactional use cases that require managing real-time data flows.
Advanced approaches to data fabric from companies like Nexla can help manage real-time integration between applications to bridge data silos and reach the edge of the data landscape, where IoT devices live. The result: the integration of data across silos and the creation of a smoother data exchange and analysis flow within the organization.
Increase Business Efficiency
Data fabric helps increase business efficiency. Data fabric brings information access to users directly without the need to rely on technical users. This leaves data engineering teams free to focus on productive and innovative tasks that increase business efficiency.
By providing a singular view of all dispersed data, data fabric can help you reduce the costs associated with data management. As a result, you can save time and money. For more on cutting data costs, here’s a step-by-step article on lowering expenses with a unified data solution.
In addition, data fabric architecture provides real-time analysis and accurate data, making things easier for your information architecture and allowing data users to make right decisions through accurate analyses.
Data fabric is an emerging concept, and learning how to implement it can be a monolithic undertaking, especially without knowledge of where to start. The recent Eckerson white paper Data Fabric: The Next Step in the Evolution of Data Architectures is a great place to begin learning what is needed to implement a successful data fabric architecture. It discusses how data fabric is different from traditional data technologies like data warehouses and data lakes and answers burning questions such as how data fabric works with existing frameworks instead of replacing them and how you can leverage your pre-existing tools to start building your data fabric solution.
Data fabric is rapidly becoming the future of data and the foundation of a unified data solution. Learning how and why this is the case is essential to the growth of any modern enterprise, but you don’t have to handle this task alone. Nexla provides an advanced approach to fabric by providing an all-in-one tool for integration that can manage real-time data, helping you reach your data fabric goals quickly.
If you’re ready to get started on your data fabric journey, Nexla can help. Get a demo, or book your free unified data solution strategy session today. Check out the Eckerson white paper for free, or for more on data and data solutions, take a look at the other articles on Nexla’s blog
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