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  1. What Is
May 18, 2016updated 22 Sep 2016 12:02pm

What is Big data as a Service?

CBR removes some of the complexity to reveal why this is an analytics trend to look out for.

By James Nunns

The area of big data has many different subsets that can be complex to understand, with Big data-as-a-Service falling into an area that bridges cloud and data analytics.

Big data-as-a-Service, or BDaaS, is a way of accessing analytics tools or information from an outside provider. This can help organisations to gain insights into the meaning of data so that they can gain competitive advantage by improving customer relationships and business decision making.

BDaaS is designed to help businesses to free up resources by taking advantage of tools that are being provided by an outside organisation.

Big data

Like Software-as-a-Service (SaaS), it can take the form of software tools that aid with data processing, or it can be a contract for the services of a team of data scientists.

Companies such as Blue Yonder provide cloud-based predictive applications for retail, the benefit of this is that many businesses don’t have access to data scientists, nor do they have the infrastructure that could support high-end analytics tools.

By using BDaaS a company can send their data to an outside company to be processed and returned to them with the insights that have been requested.

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Like SaaS, BDaaS is a form of managed service that often relies upon cloud storage in order to provide data access to both the outside analytics company and the company that owns the information.

Companies can use BDaaS as a way to monitor large SEO or Web content campaigns, while other examples of use cases can see it being used to monitor and predict stock requirements.


The area has gained increased interest over the past couple of years as companies have looked to leverage their data in a way that doesn’t create costly overheads and rely upon a complex installation and integration process.

Simply put, BDaaS is an ideal way to remove the tech complexity from doing data analytics, leaving the business to focus on simply using the data insights to improve its performance.

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