You can tell that an idea from the IT world has “crossed the chasm” when you start to see it featured regularly in the mainstream media. That was certainly the case with cloud. The same thing is now happening with data—it has captured the attention of the business press because of the central role it plays in the success (or failure) of companies in our digital age.
For example, a recent article in The Economist notes that in today’s economy, “the world’s most valuable resource is no longer oil, but data.” The article describes how vast pools of data are giving a handful of companies, especially cloud pioneers like Amazon and Google, a massive competitive advantage. It’s safe to assume that enterprises across all industries are working hard to catch-up with the leaders as they race to maximize the value of their own data.
And data hasn’t just changed quantitatively, it has changed qualitatively too. Compared to the data sets that IT teams were managing just a few years back, enterprise data is now:
- More Distributed. Data no longer just lives in your data center. Enterprise data is now distributed across multiple clouds.
- More Diverse. New data sources and new data types are complicating data management.
- More Dynamic. Because data sets quickly grow and change, it’s difficult to keep up—or even keep track of where data is and where it came from.
The challenges of a data-centric world require new thinking and a new approach to data management, one that works across hybrid clouds that span on-premises data centers and multiple cloud environments.
Multi-Cloud is Here to Stay
Dependence on multiple cloud providers for IaaS, SaaS, and other services is already a reality for most enterprises. According to the RightScale 2017 State of the Cloud Survey, cloud users are running applications in 8 clouds on average; 85% of enterprises have a multi-cloud strategy. Even users of AWS—the dominant IaaS player—aren’t putting all their eggs in one basket. IDC found that 56% of AWS users reported using other public cloud IaaS services alongside AWS*.
If you think this situation is likely to sort itself out as the cloud continues to mature, there’s plenty of evidence to the contrary. Big cloud players such as AWS, Google, Microsoft, and IBM are working hard to differentiate their services in areas such as Internet of Things (IoT), cognitive computing (AI), and data archival. There are likely to be good reasons for enterprises to continue to use services from multiple cloud players—even processing the same data in different clouds using different tools.
The emergence of multi-cloud is important because the more cloud locations you use—the more distributed your data is—the more challenging data management becomes. You run the risk of having data siloed in every cloud, without a complete understanding of the data assets you have and where they are stored.
Diversity is Increasing
There are several ways to think about data diversity. The first is the staggering number of applications and other data sources enterprises are now dealing with: traditional and new enterprise applications, SaaS applications, customer-facing cloud applications, social media and web data, Internet of Things (IoT) data, mobile and real-time data, and so on. The diversity of sources matters because you will need to effectively manage the data generated by multiple applications in order to leverage it to your greatest advantage. And you must be able to protect and secure each data set appropriately.
A second way to think about diversity is where and how data is stored. Most IT teams are versed in managing block and file data (corresponding to structured and unstructured data), but object storage—the lingua franca of many cloud services—is much less familiar. How do you convert existing data to an object format so it can be processed in the cloud? What if you need to go in the other direction?
Data is More Dynamic Than Ever
Those of us in IT are used to data growth, but data isn’t just growing: the rate of change is more rapid than we’ve ever seen before. This increase in the dynamism of data is due to today’s data-centric business models combined with new data sources that generate output continuously, such as social, IoT, and mobile.
This data is often processed in real time to gather insights or detect problems. In these streaming environments, the speed at which data can be accessed becomes critical. Having this data in the right place at the right time with the right capabilities to extract value from it can give businesses whole new capabilities.
Data Management for a Digital Economy
NetApp has been helping companies change the world with data for 25 years. We created the NetApp Data Fabric to help meet the challenges of a data-centric and inherently multi-cloud world. The Data Fabric simplifies data management across all your data centers and cloud locations, delivering consistent data services and full data visibility with superior access, control, protection, and security, allowing you to get diverse data sources under control.
If you need to move data to and from the cloud, or keep cloud and on-premises data in sync, Data Fabric services make it simple, eliminating the need for complex and error-prone manual operations. Because the Data Fabric is fast and efficient, it saves both time and money. Workflows that once seemed impossible become routine.
Discover how NetApp can help you manage your data in a multi-cloud world, and don’t just take our word for it—watch this video to see how customers like TechnologyOne are delivering new cloud services using NetApp data management technology.
[*] IDC, Amazon Web Services IaaS Storage Usage Trends, 2016, Jul 2016, Doc # US41575916