Over my thirty-year career, I have seen data analytics grow and innovate at a rapid rate. We have seen several developments that have seen analytics grow in leaps and bounds to come to the forefront of tech. Part of the reason for this is that analytics has been able to incorporate technological developments to keep with the demands of businesses. The versatility of analytics has allowed them to take advantage of AI and machine learning, as well as the on-demand economy, which brings me to the topic of this blog. On-demand analytics, what is it and how will it change the way we provide data analytics?
To understand the implications of on-demand analytics, we need to take a look at on-demand services, as a whole. According to Techopedia, cloud computing has paved the way for the provision, integration, access and deployment of mission-critical applications using the cloud where signing up is all a user needs to do to gain service. Put simply, on-demand services allow organisations to access sophisticated, high-end technology over the cloud, by simply signing up with a provider. Hence, on-demand analytics allows organisations to access data analytics services, including hosting and administration only when they need to. On-demand analytics allows organisations to gain the benefits of analytics without having to expend resources, making it accessible to more companies than before. The benefits of real-time analytics are now accessible to companies of different sizes.
On-demand analytics is part of a wider category of real-time analytics with the other type called continuous analytics, which is more proactive than its on-demand counterpart. The analytics platform runs in the background and alerts users with a steady stream of updates. Naturally, the main difference between on-demand and continuous analytics is that the former requires a query or ticket to start working, while the latter provides updates in real-time.
While on-demand analytics is a relatively new service, it is an exciting prospect because of the immense potential it has to transform the way analytics services are executed. Traditionally, big data analytics requires a sophisticated technological infrastructure, which require a massive investment from the company. On-demand analytics changes all that because cloud computing takes care of the backend operations that normally requires a lot of processing power. This makes data analytics more accessible to smaller or medium-sized companies who have sizable data to crunch.
One of the biggest benefits of on-demand analytics is the option to neatly integrate data analytics into their operations due to its scalable nature. On-demand analytics brings with it unprecedented flexibility, so organisations are free to scale up or scale down operations when they need to, and even stopping services when they need to. In other words, organisations have the option to pay only for the work done. Indeed, many analytics providers, like SAS, have built their on-demand services around this flexibility. In other words, organisations can enjoy the benefits of data analytics, like a better insight into the market and lower operation costs, but with a more flexible payment plan.
With on-demand analytics, organisations need only sign up with a proven provider to get the services they need. Of course, on-demand analytics still requires an investment of time and resources, but the barrier to entry is much smaller (some would say it is non-existent) thanks to the cloud infrastructure of data analytics. Of course, on-demand analytics is not just a game-changer for organisations, but also analytics providers because their clientele can provide services to organisations based around the world – they are no longer restricted to their home country.
On-demand analytics is changing the way analytics services are provided. Thanks to the power of cloud computing, analytics is promising to change the way organisations receive analytics services. This has some exciting implications, and I fully believe that analytics in the future will be more agile and dynamic than ever before. However, there are some precautions to be mentioned because cloud computing is so integral to the service. For example, on-demand analytics can be vulnerable to the pitfalls that are common to cloud computing-based technologies. Hence, organisations must first consider some of the risks before investing in it. They must also work with an on-demand analytics provider with years of experience in the industry and who can negate the risks to maximise the benefits.