If you’re venturing into the world of big data, you may have heard the term Analytics as a Service. If you’re confused by what this actually means, our guide is here to help.
At its most basic AaaS refers to the practise of using Web-based technologies to carry out analysis of big data, opposed to the traditional method of developing an onsite hardware warehouse to collect, store, and analyse the data.
For many years, IT organisations around the globe have been collecting and storing large amounts of data. Now, as the way businesses operate has shifted and changed, computer scientists are being asked to perform analytics so that the data can be utilised effectively. This presents some difficulty, as performing analytics can be intensive on a businesses’ resources – both man-power and running costs as traditionally a business would need to set up the internal hardware and software to carry out the needed analytics on site.
This is where AaaS is helping to improve things for businesses. AaaS is just one part of a much wider range of services, all with very similar names. These include Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). What all of these have in common is that they are models which replace traditional onsite systems with Web-based ones. With AaaS, for example, instead of developing a large internal warehouse full of software – businesses can look to providers who offer access to a remote analytics platform for a regular fee.
The new set-up that AaaS provides allows clients to use a particular analytics software for as long as needed, and can be more cost effective and less labour intensive when compared to the traditional way.
Because of this, AaaS is becoming a valuable asset for many businesses. Organisations that need to carry out more analytics may need many more additional servers, amongst other kinds of expensive hardware. This also means they need to hire a lot more staff in their IT departments to implement and keep these analytics programs instead. So, using AaaS, helps to bypass these new costs and business requirements.
Outsourcing all of the work may not be the only solution for business, however. Increasingly companies are opting for a mixture of both AaaS and more traditional methods. This kind of hybrid system, businesses use what they have on site at their disposal for analytics but outsource other components through the web, gives the modern business more choices and solutions for analysing their big data.