Digital transformation is more than shifting the adoption of technology in your organisation. It involves various complex applications that lead to the increase in data volumes and workloads. Significantly, an approach termed as data fabric has emerges as a solution to this complication. Basically, data fabric is an architecture that improves data management by reducing data complexity and enabling agility. The effectiveness of data fabric approach, however depends on its abilities to meet numbers of principles. What are the principles that define data fabric?
The principles that define data fabric can be divided into:
1. The way data is stored (Scale, performance and volume)
- Data fabric should give linear scalability where fabric is not be limited by number of files, concurrent client access and increase in data volumes.
- Data fabric is designed to ensure data consistency so that data is manageable across multiple environments regardless its location.
- Distributed metadata across all data storing nodes should be supported in the fabric to prevent bottlenecks.
2. The way data is accessed (Accessibility)
- Data fabric needs to support different data types and access protocols to allow organisations to easily access data from everywhere, anywhere at any time.
- Multitenancy is essential in data fabric such that it gives organisations the ability to create logical separations for administration, access, update, and execution.
- Data fabric should provide support for integrating data streaming in order to easily integrate data in transit with data at rest.
3. The way data is distributed (Distribution)
- It is necessary for data fabric to give distributed location support where it can be installed and deployed in any location (any environment) across the entire infrastructure.
- Data fabric should have location awareness so that distant data can be accessed, addressed and locally replicable.
4. The way data is secured (Security)
- Data fabric need to provide data backup and recovery capabilities. This feature allow organisations to deal with issues or cases without worrying about data loss event.
- Data security within the fabric should be emphasised to prevent data compromise or data breach.
With many applications being introduced to the market and claimed as data fabric approach, organisations are in need to understand these principles such that the outcomes of data fabric can be achieved.
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