What is Analytics as a Service – and what are the benefits?
We thought it a good idea to take a bit of a step back and look at the terminology we use. So let’s start with an understanding what is Analytics as a Service (AaaS) and what are the benefits. You may feel a bit like being told how to suck eggs, but do stick with us. For everyone else who isn’t sure, we hope this helps put AaaS in context for you.
Analytics as a Service is where you use a solution, in this case data analytical software, provided over the web. AaaS is in the same group as similar acronyms which include:
- Software as a service (SaaS), where you use an application available online
- Infrastructure as a service (IaaS), where you use typical IT systems available online
- Platform as a service (PaaS), where your applications can be developed online
The ‘as a Service’ element of the term tells you they all share a same basic idea. You use a web-based alternatives to buying, installing and maintaining your in-house IT systems.
The benefits of AaaS
This approach to using technology can bring significant benefits in terms of:
- Speed – the service is available instantly (or at least very quickly)
- Cost – You pay a low subscription fee instead of making large upfront expenditure on software and hardware. You can also cancel the fees when you no longer need the service.
- Flexibility – the amount of user licences you need can be increased or decreased
- Maintenance – upgrades and resolving issues are undertaken by your provider
Where AaaS scores really well is taking what can be a very intensive process out of your internal systems. Analytics software and services can chomp through your server resources. This can mean you have to find more hardware or risk the wrath of unhappy staff unable to do their work. AaaS also reduces the need for your your support team to build niche skills, avoiding problems in planning your staff resources. So you can see just from the two point above that AaaS is an attractive alternative.
Apart from this, AaaS provides the same range of solutions as you would find in a traditional in-house approach. Data cleansing, mining, predictive analysis, AI, and of course organising and presenting data are just a few features you will find. But with AaaS you won’t need dedicated warehousing or a support team.
Using AaaS also resolves a common question faced by many organisations. You know your data will contain some valuable insights, but how can you reach that information? Leading-edge analytical solutions used to also mean huge investment in your teams and your systems. Now you can adopt a more hybrid approach, combining external data science expertise in conjunction with existing capabilities. This method would bring you faster, more productive and cost efficient results.