Together with Software-as-a-Service (SaaS), Data-as-a-Service (DaaS) became mainstream some time ago. While Salesforce.com was the one who made SaaS so popular, DaaS has long been used only in web mashups. Both data and the software processing them were combined in the same package. Today data are commonly provided on-demand and is available to users regardless of their geographic and organizational separation from a provider.
The rise of the Internet meant easy access to almost any kind of information. With so much information available at any time it became difficult to determine their quality and to use them effectively. The purpose of DaaS models and techniques is to enable users to access relevant and accurate information that are usually stored in a corporate data center or in a public cloud. Regardless of the type of the cloud the data are stored at, the services include the same options.
DaaS is not a new concept, but is definitively getting more popular in business environments. In 2007, Factual launched data platform that contained all kinds of information. InfoChimps offered similar service in 2008.
Three most often quoted benefits of DaaS approach are:
- Agility – DaaS provides easy and efficient access to real-time data enabling immediate action without necessarily understanding the actual data.
- Affordability – Providers offer flexible prices, so a variety of users have the opportunity to use the full capacity of data collection.
- Data quality – Data services regulate and sort the relevant data thus providing the necessary quality of the requested information.
In the modern business it is highly important to have an accurate piece of information in requested time. DaaS offer the access to the freshest and most relevant information which is necessary for the business to run seamlessly. With the precise information about consumers for example, it is possible to improve customer service or product and thus gain higher profits.
In relation to Data-as-a-Service models three other terms that should be mentioned.
Database as a service
– refers to regular enterprise database which is stored on a remote server and is managed by a service provider for a monthly or annual fee. This way of external data management brings multiple benefits to company – it’s cheap, efficient, accurate and simple.
Linked data as a service
– refers to connecting information semantically on the basis of resources and usage. The intelligent data management has become highly important for the businesses, so the companies started to connect their own internal information into an intelligent network – Linked Enterprise Data.
Big data as a service
– advancement of technologies and computing power resulted in huge amounts of unstructured data that are difficult to process. To facilitate management of big data the cloud offers solutions in the form of tools and programs that store and analyze petabytes of data such as Hadoop.