The IT “as a service” model is working well for organizations. It enables them to start small and scale quickly as IT demand increases. And IT as a service’s value is not limited to start up companies. Organizations of all sizes want greater flexibility to expand, contract and move IT resources. Most of the “as a service” success focuses on Software as a Service (SaaS) and Infrastructure as a Service (IaaS). But each of these service models needs to be fed with data, and data, unless it can also be delivered as a service, has gravity.
The Data Gravity Problem
Both SaaS and IaaS allow organizations to start up and turn down IT services as needed, with quite literally the click of a button. Data doesn’t work like that. When an application or service needs data, its data needs to be copied from something to something. This might mean copying data from an on-premises storage infrastructure to a public cloud or it could me copying it to a private cloud, also on-prem. In either case data has to move. And in both cases, when the service is ready to be turned down, that data needs to be removed.
The first challenge with data gravity is that it takes time to copy data from point A to point B. If point B is the public cloud, latency and bandwidth impact copy times. The second problem is, of course, the cost of the capacity the data consumes while stored on the service. The first problem, time, makes the second problem – cost – worse. Since it takes time to copy data, organizations are more likely to leave data in place even after the current service is no longer needed. Leaving data in-place for an extended period of time, especially if that place is someone else’s data center (a.k.a. the cloud), increases the organization’s risk exposure to that data being stolen or hacked.
The final problem is potentially the biggest, but unfortunately the most overlooked – efficiency. The movement of data and the connection of this data to the service once moved is typically a manual process driven by an IT professional who has more than enough tasks to do.
It’s Time for Data as a Service
Data as a service creates virtual copies of data to support the various processes and applications that need them. Essentially as data as a service solution makes one (or two for disaster recovery) golden copies of production data. Those golden masters then feed all the other processes that need access to data. For example, if the organization decides it needs a third copy of data for long-term data retention, the golden master can feed a backup process. If test/dev or dev/ops needs a copy of data for ongoing application development the data as a service engine can routinely present a virtual copy of data from the golden master without consuming any additional capacity. The only capacity increase is when parts of the golden master are changed or added. The golden master could feed analytics engines or a reporting process, all while keeping two master copies of data.
Organizations are building applications and infrastructures that are extremely portable. It’s time for data to follow suit. With “Data as a Service” in-place, organizations can reduce the time, cost and risk associated with feeding SaaS and IaaS processes while increasing data efficiency.
To learn more about Enterprise Data as a Service, register to watch this instructional video that walks you through the enterprise data as a service concept and shows you how to get started.
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