Wednesday, June 12, 2019

Word of the Day: data management-as-a-service (DMaaS)

Word of the Day WhatIs.com
Daily updates on the latest technology terms | June 12, 2019
data management-as-a-service (DMaaS)

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.

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 and G-Suite. For example, none of these companies require customers to install or manage infrastructure - virtual or physical - to provide or consume the service. Companies using such services simply tell the vendor (usually via their interface) their specific needs, such as how many users should be registered and what amount of storage each user will need. The infrastructure required to provide that service will be automatically provisioned and managed by the vendor.

Data Management-as-a-Service leverages cloud services to provide scalability, insights and accessibility to a company's various sources of data. This central collection of data is then leveraged to provide data protection and additional services. Data sources include file servers, application servers and database servers, including virtual machine (VM) databases as well. Most companies also have data in one or more cloud providers, and on many desktops, laptops and mobile devices. A comprehensive data management solution protects and manages data from all sources in a single cloud-based system; however, there are data management solutions that only protect and manage a subset of these data sources.

The additional services mentioned above include proactive compliance, data analytics, legal hold and centralized search. A centralized view across all data sources provides the best viewpoint for many of these services. For example, if an electronic discovery request asks a company to find and hold all instances of a given employee's work, being able to perform a single search across servers, laptops and cloud instances makes fulfilling that request much easier.

Benefits

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.

Quote of the Day

 
"Rather than the large recurring capital investment that most IT systems require, DMaaS typically can be an operating expense that goes up and down based on how much of the service the customer is consuming, such as how many terabytes (TBs) of data is stored or how many users' laptops are being protected." - W. Curtis Preston

Learning Center

 
Introduction to enterprise master data management
In many companies, this master data is kept in many overlapping systems and is often of unknown quality. For many organizations, this situation constitutes a dilemma - it becomes increasingly difficult for organizations to implement change.

Master data management as a service-oriented architecture enabler
Learn how master data management (MDM) provides service-oriented architectures (SOAs) a single location from which to manage data entities that are critical to enterprise processes.

Augmented data management draws more enterprise interest
Much like augmented analytics, augmented data management is an emerging trend. It uses AI and machine learning to automate manual tasks, enabling data professionals to make quicker decisions.

Hot data storage technology trends for 2019
We identify data storage technology trends that will be hot in 2019 -- cheaper and denser flash, AI and machine learning storage analytics, and multi-cloud data management -- and weren't quite hot enough yet in 2018. Read our annual hot and not-hot-yet tech lists.

What is data separation and why is it important in the cloud?
Many users avoid the public cloud due to its multi-tenant nature and data security concerns. Learn how data separation can keep your data safe.

Quiz Yourself

 
The majority of stakeholders want access to current information as well as ________ data.
a. historical
b. historic

Answer

Stay in Touch

 
For feedback about any of our definitions or to suggest a new definition, please contact me at: mrouse@techtarget.com

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