Data Management-as-a-Service (DMaaS) is a type of cloud service that provides enterprises with centralized storage for disparate data sources. The label "as-a-service" references a pay-per-use business model that does not require the customer to purchase or manage infrastructure for data management. In this business model, the customer backs up data to the DMaaS service provider. This is typically done by installing agents on the data sources being backed up, although in the case of cloud data sources, a simple authentication process may be the first step.
DMaaS is typically an operating expense that goes up and down based on how much service the customer is consuming. It is technically possible to provide DMaaS using on-premises infrastructure or a private cloud offered by the DMaaS vendor, but all infrastructure must be provided and managed by the DMaaS vendor to be considered a service. Although it may be possible to do DMaaS this way, it is prohibitive to do so for logistical and cost reasons.Content Continues Below
How DMaaS works
As the name implies, DMaaS must be done as a service – it is not DMaaS if a company must purchase, install and maintain significant amounts of infrastructure to perform data management. The “as-a-service” moniker should be in keeping with the traditions of services that have created and defined the concept, such as Salesforce.com, Office365
Data Management-as-a-Service leverages cloud services to provide scalability, insights
The additional services mentioned above include proactive compliance, data analytics, legal hold
Three advantages to DMaaS hosts over other data management solutions include:
- A complete DMaaS system can protect all of a company’s data assets while drawing additional value from it and reducing cost at the same time.
- The centralized storage of data that DMaaS requires eliminates waste and facilitates other parts of the business.
- Using a data management service (versus purchasing and maintaining the infrastructure to do it yourself) reduces capital expenditures and makes data management costs much more predictable.