Data has become central to business success today as businesses use data and analytics to drive both operations and strategic decision-making. At the same time, the data itself has become more scattered and it's become challenging to use it effectively. The useful data grows constantly and it takes on many forms, rather than simply being structured and relational. With data stored both on-premises and in the cloud, moving data between environments so it's accessible where and when it's needed is a key challenge.
In fact, surveys show that the inability to effectively move data between environments and manage it wherever it resides is a key factor delaying businesses in implementing cloud architectures.
Using Cloud Means Traditional Methods Don't Work
Traditional data transfer methods such as FTP simply don't translate to the cloud. Enterprises need to use new methods that offer the speed and control the new architectures demand and find ways to support data sharing within a public cloud's applications, between the public cloud and the private on-premises environment, and between multiple public clouds.
Finding a single solution to these issues that works across the company is made more difficult because every application typically has its own approach to storing data. But crafting a data transfer solution on an application-by-application basis isn't scalable, supportable, or dynamic enough to support the needs of a data driven enterprise.
That means you need to find a data transfer solution that can overcome the application-level data challenges. Those problems go beyond simply the fact that some applications store data in SQL databases while others use NoSQL databases. Different applications can store the same data in different formats, or duplicate information stored elsewhere. Simply transferring everything can mean unnecessary volume, cost, and time.
In addition, not all data is centrally stored any more. Internet of Things devices create their data at the network edge. That data may need to be moved from the edge to the center and back out beyond the corporate network to the cloud, again adding time.
And none of this data is static. The content changes, but so does the format. Adding and deleting fields can lead to incompatible applications, or, worse, applications that misinterpret the data they receive.
There are also the challenges of protecting the data, both while it's being transmitted and when it's used at its destination. Maintaining confidentiality and integrity is tough even when data doesn't go anywhere; when it moves across platforms that all use their own tools and controls, applying policies consistently can be extremely difficult.
Ultimately, for hybrid data centers to be successful, they need a way to make data formats consistent, streamline transport, and effectively implement data governance.
A Data Fabric Spans the Data Environment
That's where a data fabric like NetApp comes in. Using a data fabric allows an enterprise to unify its data from the network edge to data center to cloud. The data fabric provides a framework to simplify data movement and data access while ensuring the appropriate data protection. By applying a common model for data management, data transport, and data formats, using data across platforms becomes seamless and efficient.
Data management used to be about keeping data safely stored in the data center. Today's data management needs to look beyond the data center to solve the challenges of moving data to the network edge and the cloud. dcVAST can help you use the NetApp data fabric to meet that need. Contact us to learn more about how NetApp can solve your data movement challenges.