Data as a Service (DaaS)

Data as a Service (DaaS) is an information provision and distribution model in which data files (including text, images, sounds, and videos) are made available to customers over a network, typically the Internet. The model uses a cloud-based underlying technology that supports Web services and SOA (service-oriented architecture). DaaS information is stored in the cloud and is accessible through different devices. The service also offloads the downsides of data management to the cloud provider. 

DaaS allows for, but does not require, the separation of data cost and usage from software or platform cost and usage. Hundreds of DaaS vendors, with various pricing models, exist worldwide. Pricing can be volume-based (a fixed cost per megabyte of data in the entire repository) or format-based (for example, a fixed price per text file and another fixed price per image file).

High-speed Internet service has become increasingly available to support user access from more areas around the world, making DaaS an attractive option to a wider audience. Similarly, organizations with an excess of data may have a difficult and expensive time maintaining that data, making DaaS a popular solution. The evolution of SOA has greatly reduced the relevance of the particular platform on which data resides.

Examples of DaaS

DaaS offers convenient and cost-effective solutions for customer- and client-oriented enterprises. For instance, Fidelitone, a supply-chain and logistics management company, employed ARI's DataStream DaaS solution to deploy parts catalogs into the customer channel.

A few other examples of DaaS providers include:

  • Urban Mapping, a geography data service, provides data for customers to embed into their own websites and applications.
  • Xignite is a company that makes financial data available to customers.
  • D&B Hoovers provides customers with business data on various organizations.

Benefits of DaaS

Benefits of DaaS include the following:

  • Ability to move data easily from one platform to another.
  • Avoidance of the confusion and conflict that can occur when multiple "versions" of (supposedly) the same data exist in different locations.
  • Outsourcing of the presentation layer, reducing the overall cost of data maintenance and delivery.
  • Preservation of data integrity by implementing access control measures such as strong passwords and encryption.
  • Avoidance of "vendor lock-in."
  • Ease of administration.
  • Ease of collaboration.  
  • Compatibility among diverse platforms.
  • Global accessibility.
  • Automatic updates.

Challenges of DaaS

Challenges to DaaS include concerns with privacy, security and data governance. Challenges in privacy revolve around the fact that the data shared may often include information pertaining to mission-critical applications. Concerning security, the data for mission-critical applications may be left venerable if the DaaS vendor’s security is not up-to-par. It may also be difficult to ensure data governance among data between a DaaS environment and an organization.

DaaS’s future

Information management specialists believe that as more companies figure out which data assets they can rent for competitive advantage, the DaaS market will continue to expand. DaaS is expected to be a launching point for both business intelligence and big data analytics markets, according to Gartner. Gartner also still sees the DaaS market growing as more organizations start seeing DaaS as a fitting way to manage mission-critical data.

DaaS is closely related to Storage as a Service (SaaS) and Software as a Service (also abbreviated SaaS) and may be integrated with one or both of these provision models. As is the case with these and other cloud computing technologies, DaaS adoption may be hampered by concerns about security, privacy and proprietary issues.

This was last updated in May 2019

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