More data than ever. More data types than ever. More data locations than ever. Enterprises have benefited from the influx of big data, but many still struggle to manage all available data sources. What’s more, BI Survey reports 50 percent of companies it surveyed believe the number of data sources they use to inform their decision-making will continue to increase.
As a way to better organize and manage this valuable resource, some businesses have begun to explore data fabric as a solution. But what is data fabric, and what value can it bring to your organization? It’s time to find out.
A data fabric is an abstraction layer that encompasses all the data centers and data sources across your entire data architecture. This layer manages all data locations and types held by your enterprise. It captures critical information about each data source, including who created the data, who changed or modified it, where it resides, and when it expires, as well as other provenance and change information. These qualities make the data fabric, or data plane, a trusted source and make data easily available to the internal audiences who need access to it.
The rise of big data offered enterprises a virtually unlimited supply of information, and data lakes were formerly the storage architecture of choice for many businesses. The challenge, however, came in trying to scale data lakes as storage costs increased.
As cloud services evolved, storage became more cost-effective. But soon a new challenge became clear: data located in multiple data centers and moving across locations. These multiple locations and the need for mobility created performance and governance issues.
As an abstraction layer, the data plane, or data fabric, offers a practical solution that allows a comprehensive view of available data, easy access by all parties that need to use it, and uncomplicated management.
Enterprises have found a growing gap between what they expect from their data operations and what’s being delivered. Data fabric offers a new approach to modern data center architecture that bridges that gap by removing blind spots and simplifying data management. The abstraction layer offers visibility and awareness of all available data sources: when new sources are added, for example, users are aware of the addition.
The underlying processes of a data fabric focus on automation, which makes ingesting, curating, and integrating data sources far simpler. It also simplifies the application of security and governance policies. Additionally, when data moves, those same security and governance policies move with it to its new location.
If your current data architecture is limiting your business operations, it may be time to add a layer of data fabric. A few questions can help identify whether your business needs a new data model:
Big data has quickly become one of the enterprise’s most critical assets. Data sources will only continue to grow, and businesses need architecture that can scale to match, plus a simplified management process that addresses the challenges of governance, security, and portability of data repositories. A data fabric offers a single source of trusted data that can be easily accessed by the stakeholders and stewards of that information in your company.
As data sources, locations, and platforms grow, so will the need for a uniform data management layer. The comprehensive view data fabric offers is the most practical means for unifying your data. What is data fabric? The tool that will future-proof your big data operations.
Learn why Forrester named Hortonworks DataPlane Service a strong performer in big data fabric by downloading this report.