Data Fabric is another hype that you may have heard a lot about recently. It has evolved to symbolize enterprise data integration and management in recent years. The term “data fabric” basically refers to a unified data management architecture and a set of capabilities that provide consistent capabilities for connecting data endpoints and enabling end-to-end data management capabilities.
What is Data Fabric?
Data fabric is a complete data integration and management solution that includes architecture, data management, integration software, and shared data to assist organizations in managing their data. It offers an integrated, seamless user experience and data access for any member of an organization, anywhere in the world and in real time.
It is intended to assist organizations in solving complex data problems and use cases by managing their data, regardless of the applications, platforms, or locations where the data is stored. In a distributed data environment, data fabric enables frictionless access and data sharing.
Why Do Modern Companies Need Data Fabric
Organizations are dealing with increased scalability and complexity. The IT systems are advanced today, allowing them to manage existing applications as well as modern applications powered by microservices across disparate environments. Implementing a data fabric is one way organizations are addressing these data management challenges. It enables businesses to make better use of their existing data architectures without having to structurally rebuild every application or data store.
Data fabric enables the management of multiple environments at the same time, including on-premises, cloud, and hybrid. Also, providing access to accurate data and enabling unified and simplified data management by eliminating the need for multiple tools. A data fabric allows you to create a global and agile data environment capable of tracking and governing data across applications, environments, and users. For example, when objects move from one environment to another, the data fabric notifies each component and manages the necessary processes, such as which process to run, how to run it, and what the object’s state is.
When data fabric is integrated into a single unified platform, it supports the following key capabilities
- Unified Data Semantics –
A single workspace for all document types simplifies the business purpose and establishes a single source of truth for a consistent analytics experience.
- Data Catalog –
A well-organized inventory of the organization’s data assets.
- Data Management And Governance –
Setting internal standards, data policies that govern how data is collected, stored, processed, and disposed of is what data governance implies.
- Data Engineering –
Process of designing and constructing large-scale data collection, storage, and analysis systems.
- Integration & Distribution Of Data –
This usually involves extracting or retrieving data from any trusted source and then making the data accessible for further processing towards the consumer.
There are numerous advantages to using data fabric over data management techniques
- Visibility and insights into data
- Excellent consistency, availability, and durability
- Enhanced data management
- Data protection and security
There are numerous use cases in enterprise operations that necessitate a large-scale, high-speed data architecture capable of supporting multiple transactions. Some of the examples are stated below
- 360-degree customer view
Providing a complete and unified view of customers via CRM systems, IVR, or a customer self-service portal.
- Simulating enterprise data
Allow engineers to rapidly and at scale prepare and deliver accurate and reliable records into data lakes and warehouses from all sources.
- Adherence to data privacy laws
By implementing an adaptable workflow and a data automation solution that ensures compliance among people, systems, and data.
- Fraud monitoring
To avoid potential breaches, protect sensitive credit and debit card information with end-to-end encryption and multi-factor verification of the original data.
Data Fabric and Artificial Intelligence
Data fabric represents a major shift in how businesses use data. Algorithms for machine learning and artificial intelligence are critical components of a data fabric design. These algorithms collect information from data as it is connected to the fabric and continuously canvas all of the organization’s data, determining its characteristics and understanding where potentially useful relationships and connections exist.
Existing applications and data can be kept in place, allowing organizations to access, coexist, and analyze the data in flight and on-demand. This enables businesses to make better use of existing data architectures and update their models in real-time without having to rebuild every application or data store structurally.
Utilizing a smart data fabric accelerates the transition to a digital future while avoiding the cost and stress of breaking and replacing the organization’s current operational infrastructure. In an era of constrained resources and ongoing supply chain issues, companies must meet new requirements for delivering effective and sustainable growth. Data Fabric can assist organizations in accelerating business transformation by utilizing technology and innovation.
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