Definition

data science as a service (DSaaS)

Contributor(s): Ed Burns

Data science as a service (DSaaS) is a form of outsourcing that involves the delivery of information gleaned from advanced analytics applications run by data scientists at an outside company to corporate clients for their business use. A DSaaS provider collects data from clients, prepares it for analysis, runs analytical algorithms against the refined data and returns the findings generated by the algorithms to the customers.

DSaaS typically requires clients to upload their data to a cloud database or a big data platform, where the service provider's team of data engineers and data scientists can work with it. Examples of DSaaS applications include sales and marketing analytics around things such as which customers of a company are likely to buy more products and which may defect to rival suppliers; analysis of internet clickstream data for planning online advertising and marketing campaigns; assessing customer records to inform customer service representatives in call centers about which promotional offers callers are most likely to respond to; and social media analyses that help enterprises gauge the public's perception of their brands.

The results of these analyses can be delivered to executives and other users at clients in reports and business intelligence dashboards, or as data products that get embedded in operational systems, as in the case of a call center application with built-in prescriptive analytics.

Data science as a service is a potential way for organizations to cope with a shortage of data scientists and other skilled data analysts. Businesses increasingly are looking to predictive modeling, data mining and other forms of analytics to provide business insights they can profit from. But as the awareness of the benefits of advanced analytics grows, the number of trained data scientists isn't keeping pace, leaving many enterprises unable to find enough to lead all the analytics projects their business operations need. In addition, the scarcity of data scientists has driven up the cost of hiring for the position. DSaaS gives organizations access to analytics resources for specific data science applications without requiring them to hire or train their own analysts.

This was last updated in July 2016

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Do you think data science as a service could help enterprises cope with the shortage of data scientists?
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In the short-term maybe..
Right back to the early days of data analytics, when someone came up with a new technology for static reporting or dashboards, service companies and start-ups grabbed at the prospect of this new breed offering specialist services to laggard big corporations. There is some uptake closely followed (after early adopters trumpet success) by a move to pull it in-house.
In time, the innovative start-ups become a means to help the big corporations with their shopping - the strategy remains in-house and more commodity services are bought from outsourcing providers.
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