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  /  Big Data   /  Understanding the Importance of Leveraging Data Fabric in Businesses

Understanding the Importance of Leveraging Data Fabric in Businesses

Most of us working in IT or non-IT sectors must have heard about ‘data boom’ or ‘storage is growing’. The general reaction to these is an assumption about growth in data capacity needs over the years. However, it actually refers to storage growing over several different vectors like performance, protocols, hardware types, and locations. And the solution to this is data fabric.

Identified by Gartner as one of the “Top 10 Data and Analytics Technology Trends for 2019.” data fabric is perhaps a new term with immense potential and importance. While the companies and businesses are expanding, their usage of the number of applications and the need for a better data solution rises too. When data is isolated and transferred to data silos, it becomes stagnant and inaccessible. Legacy and bureaucratic systems make it more difficult to access such data, resulting in low productivity and efficiency. Data Fabric eases the processing, management, analysis, and storage of almost any amount of data from a multitude of sources. Then it enables applications and tools to access that data using an array of interfaces such as NFS (Network File System), POSIX (portable operating system interface), a REST API (representative state transfer), HDFS (Hadoop distributed file system), ODBC (open database connectivity), and Apache KAFKA, on real-time.


What is the purpose of Data Fabric?

So basically what data fabric does is, it sews together data management, data placement, performance optimization, and access management to assist storage resources to be automatically provisioned to requesting users or applications in a self-service manner. This allows data to move between storage systems within a data center or to the cloud without changing user processes. It also means that it can have a specific set of quality of service guarantees associated with it, so the data responds to user requests in a consistent fashion. Lastly, it means users and devices can write or read data from the fabric with the access protocol of their choice.

One might argue about the necessity for the data fabric system when we already have data lakes and data warehouses. But here is the fact, although data lakes and warehouse store the data itself, they don’t give us the portrayal of the data in motion. This is beneficial when we require to have cohesive, flexible management and follow up. Data fabric also provides speed, scalability, and reliability while supporting multiple locations like edge, cloud computing platforms like AWS, Azure. It has the potential to bring data from established systems under the umbrella of one unified platform.


How can Data Fabric help?

Having a data fabric solves some critical challenges prevalent in the organization. These are low data availability, presence of silo-ed data, and reliance on underperforming legacy systems. Other significant benefits are:

  • Ability to connect to any data source via pre-packaged connectors and components. Thus eliminating the need for coding.
  • Provision of built-in data quality, data preparation, and data governance capabilities, sustained by machine learning augmented automation.
  • Supporting data share with internal and external stakeholders via API support.
  • Easy connection with the cloud by backing on-premise, hybrid and multi-cloud environments and faster migration between them. This reduces time to insights dramatically.
  • Future-proofing and adding flexibility to the data management infrastructure of a firm. This allows adding new data sources and points to fabric without disrupting existing connections or deployments and adapt to changing technological needs.
  • Capability to deliver predictable performance whether the data is available at a highly accessible storage location or a low-cost economy storage infrastructure. This helps the organization to optimize their data investments based on evolving app usage requirements.
  • It augments the organization’s human teams, thereby purging a lot of manual processes.

The goal of the data fabric is to reduce the storage sprawl that organizations are inflicting on themselves in an attempt to address data sprawl. It also prevents cloud platforms from being used as a gigantic data dumping platform. By seamlessly moving data between locations, in both directions, not only for backup and archive but also for cloud bursting or application migration, data fabric helps achieve the required flexibility and agility. Besides, all these features can be yielded at a fraction of cost. For an organization seeking digital transformation, this may be the best bet to understand the overall structures, unify data silos while ensuring smooth, effective data management, and have a clear vision of the same.