December 15, 2016
The concept of DaaS is not new to the market, but an increasingly important one, given the accelerating growth and complexity of data accumulated by organizations across industries. As experts explain, the big picture idea behind the DaaS model is all about offloading the risks and burdens of data management to a third-party cloud-based provider. DaaS is a way of accessing business-critical data where it resides.
DaaS is also described as productized data-driven insight on demand. As Elizabeth Press, Founder of D3M Labs, adds, going beyond the technology stack and into core business decisions, DaaS distinguishes itself from other ‘-as-a-Service’ products, because it enables data to become an active partner in human decision making.
Applied to customer relationships, for example, DaaS is a service approach in which unique data is sourced or custom built in order to create a list of prospects. This can begin with the ingestion of a company’s CRM file for measurement, customer acquisition or running models against data sources in order to identify additional propensities and behaviors.
Oracle emphasizes that DaaS is a revolutionary service that provides companies with unprecedented levels of connection to customers. DaaS is a response to the growing volume and variety of data generated in today’s digital world. Users consume data across a variety of systems and processes – data that can be used to make customer engagements more relevant and impactful. This data-driven insight helps you connect with customers across marketing and sales to virtually all areas of your business, the company shares.
Among the most important benefits of the DaaS model, professionals emphasize its cost-efficiency, agility and improved data quality.
Cost-efficiency is the most visible benefit with DaaS solutions just like any other type of a cloud-based service, which are known to be driving operational efficiency and significantly decrease costs of running any business. DaaS offsets many of the costs associated with managing and housing these complex data sets in-house: one way providers help organizations save money is on the presentation layer of their interfaces and applications. They can build them in such a way that makes it easy to change location-based and organizational assets in a fluid way.
Agility of DaaS model enables businesses to easily and quickly access necessary data in the cloud, retrieving meaningful and impactful information. The main benefits of DaaS are rooted in its cloud-based storage, enabling data flexibility for enhancement and enrichment, not mentioning lower cost of maintenance.
Since DaaS is largely maintained and controlled by a service provider rather than companies generating data, it adds to a robust layer of security and improved data quality ensured by an ‘impartial’ technology company. Oracle notes that DaaS is delivering specific, valuable data on demand.
Through DaaS model, businesses can utilize the mass of data available in their vertical to offer a better customer service and drive insights on business improvement. Availability of vertical expertise is, probably, one of the most important benefits of turning to DaaS model as it improves the accuracy of data analytics insights.
DaaS is based on the ability to integrate data through APIs, paving the way for such companies as Xignite, Hooover’s, CA Technologies, and other well-known, examples. AWS recently played a role of a DaaS provider with its initiative launched in collaboration with The American Heart Association: mid-November, the American Heart Association (AHA) announced a milestone in its strategic collaboration with Amazon Web Services (AWS) – the launch of a global, secure cloud-based data marketplace that will help revolutionize how researchers and clinicians come together as one community to access and analyze rich and diverse data to accelerate solutions for cardiovascular diseases – the number one cause of death worldwide.
As reported by the InfoWorld, when released, the AHA Precision Medicine Platform will include a vast array of curated data sets that are centrally stored, searchable, and managed on Amazon's cloud. This will enable researchers and clinicians to aggregate and analyze the data, including longitudinal cohorts, proteomic, genomic and gene expression data. The most interesting part is that AWS will not only provide the storage for data but the data itself, positioning itself as a DaaS provider.
DaaS can also be specialized to address needs of a particular industry with Internet of Things Data-as-a-Service (IoTDaaS) being an example here. According to Research and Markets, IoTDaaS constitutes retrieving, storing and analyzing information and provide customer either of the three or integrated service package depending on the budget and the requirement. Estimates suggest that acquiring (capturing and/or licensing), storing, processing, and distributing IoT data will become a $15 billion business by 2021.