Cloud Analytics is the Fastest Growing Sector Until 2023

October 25, 2019 in Analytics



Cloud Analytics is the Fastest Growing Sector Until 2023

According to reports by Mordor Intelligence and others, the global cloud analytics market is expected to grow at a CAGR of 22.35% between 2017 and 2023, from USD 11.272 billion to USD 37.816 billion. This is arguably the highest growth rate for any market right now. And it may be more impressive than it sounds, given the cloud analytics market’s already extreme popularity among businesses. 

According to the MicroStrategy 2018 Global State of Enterprise Analytics Report, about 46% of enterprise organisations rely on both cloud and on-premise analytics deployments, out of which 39% have all of their analytics on the cloud. The sector’s immense potential is resulting in several more tech and business leaders to invest in it. Here is an analysis of why the cloud analytics sector has such a phenomenal growth rate.

The need for cloud analytics

In the context of the abundance of useful data being generated and collected from numerous different sources, the demand for data analytics on the cloud can seem obvious. However, as any professional would agree, the data is unlikely to be of value without appropriate structuring and analysis. 

For instance, web analytics assists businesses improve websites to drive traffic, and data analytics helps businesses make better decisions, predict consumer behaviour and much more. Analytics also finds major use cases in forecasting, IoT, automation and Machine Learning, which all require consolidated data to improve their functioning. On-premise solutions often don’t measure up:

  • While the analysis can be performed on-site, it can require significant amounts of hardware, making the process highly expensive. 
  • Another important consideration is that the amount of data generated is exhibits noticeable volatility. Adjusting on-premise analytics to work with this changing data is a major challenge. 
  • The cloud is a much more cost-effective solution for businesses, who can then outsource the analytics to cloud service providers. The cloud is thus primarily offered as Software as a Service (SaaS). 

Advantages of Cloud Analytics

Lower costs

Even for low-end applications, the resources required to analyse data can remain very high. High-end hardware, large memory resources, etc. are required on-site. 

Human resource requirements for such kind of data processing on-site also vary, and it can be challenging to source talent with the right skill-set. Additionally, the maintenance of such hardware is quite expensive. 

Simplicity

Once a package is purchased from a cloud service provider for use by a business, data analytics processes become rather simplified. Cloud analytics platforms generally feature an intuitive user interface and online dashboard without steep learning curves. The result? Managing services, data processing and even administrative tasks are made simple.

Faster processing

A major advantage with cloud-based analytics is efficiency. There’s a staggering amount of time saved – right from when you set up an environment from scratch, the installation of hardware and software, applications, etc. However, the infrastructure for data analytics is already available to businesses on the cloud. All that users must do is connect it with an application, and the cloud starts performing its analytics functions immediately.

Scalability

Another critical advantage is that the cloud is scalable. The quantity of data our applications can generate can be subject to large fluctuations, often to a degree that an on-premise analytics environment can’t handle. While designing for such fluctuations is possible, it’s certain to be expensive and a likely waste of resources. The cloud can readily scale its operations in either direction, allowing organisations to adjust their analytical capabilities according to the amount of their data. They can scale up when there is a surge, and scale down when there is a dearth.

In conclusion

In short – cloud analytics is:

  • Cheaper, 
  • Simpler to use, 
  • Saves time and, 
  • Scalable. 

It provides valuable insights at near real-time pace – an extremely useful attribute for modern applications. The raw hardware power itself – from processing, memory, and software offered by cloud analytics platforms, remain unmatched. It isn’t a surprise then, to be witnessing the rapid growth that we have over the past few years.