Thanks to the evolution of cloud, storage technology and Big Data, there has been a barrage of as-a-service models that have gained momentum. After SaaS, PaaS, IaaS etc., the latest entrant is BDaaS: Big Data as a service.

BDaaS is making waves in the industry today, but its impact in the longer run still remains an enigma. Let’s begin by deconstructing what it really is, and what it means to use it effectively.

Bernard Marr has written an article for Forbes, titled Big Data-As-A-Service Is Next Big Thing, where he describes BDaaS as,
“A somewhat nebulous term often used to describe a wide variety of outsourcing of various Big Data functions to the cloud. This can range from the supply of data, to the supply of analytical tools with which to interrogate the data (often through a web dashboard or control panel) to carrying out the actual analysis and providing reports.”
In a nutshell, BDaaS stands for two things:

  • A highly functional ‘Service-oriented’ data architecture

  • The instantaneous growth/promise of Cloud virtualization

The former enables data management/analytics within the frame work of a complex ‘event-driven’ processor. It manages data through the Descriptive, Predictive and Prescriptive modules, each of which represent an analytical approach.
Using them, one can carry out any type of analysis that can be used for overall business growth; be it customer analytics, business innovation or risk/performance management. In fact, today, Predictive analytics has become an integral business intelligence tool across industries.
All of this, presented through cloud would mean better scalability, lower costs and better mobility, whether it is within or off premises. Moreover, in response to the velocity, volume and variety of Big Data, BDaaS offers adequate storage facility for high – speed data streaming, distributed computing, and extensive processing abilities.
For emerging entrepreneurs, BDaaS falls under the must-consider category. As an early adopter, one is endowed with the best opportunities at customization.
BDaaS is usually executed over several layers. It is inclusive of the basic infrastructure, cloud infrastructure, and storage, analytic and computing components.
The framework is usually made up of the PaaS (Platform as a service) layer, along with either SaaS (Software as a service) or IaaS (Infrastructure as a service), or both.

  • Core BDaaS – a commonly employed software; mostly Hadoop and its ecosystem (PaaS)

  • Performance BDaaS – a database ecosystem with optimized infrastructure (IaaS and PaaS)

  • Feature BDaaS – a database ecosystem with features for productivity and exchangeable infrastructure and (PaaS and SaaS)

  • Integrated BDaaS- combination of all three focusing on complete vertical integration for features and performance

Hadoop remains the dominant player in terms of the framework used. It is cost- effective, flexible and highly scalable. More importantly, Hadoop’s high resilience to faults/failures is a key advantage that BDaaS companies lookout for.
At first glance, the term ‘Big Data as a Service’ may sound ambiguous, but when you really look at it a bit deeper, the concept is rock solid.
Today, BDaaS has come a long way from traditional big data services. Entrepreneurs can employ BDaaS and enjoy better flexibility; be it structured or unstructured data, better scalability; regardless of the volume of data and better services; with a varied repertoire to choose from.
Want to know where all the BDaaS hype is headed?  Stay for the second part of this blog that will talk about the challenges and opportunities that BDaaS throws up.