Technology moves fast, particularly in the area of data analytics. More data is being created than ever before and companies are beginning to see the value in it and turn to technology to leverage this. Deploying analytics in the cloud grants businesses more flexibility and capability than traditional on-premise methods. It also means they’re perfectly placed to take advantage of the latest technologies disrupting the analytics market. Two of these pieces of technology, Predictive Analytics and Artificial Intelligence (AI), are some of the most exciting and innovative things to happen in analytics, ever. That they’re set to cause a shakeup to the industry is a staggering understatement. Their impact will be transformative.

Let’s take a look at why cloud analytics is the perfect way to take advantage of these technologies.

Predictive Analytics

To oversimplify the point, the cloud is a better environment to host and run predictive analytics in. There are a number of factors that contribute to this. Performing predictive analytics requires a lot of data, luckily, we’re not short of that, but what we do need is the access to and processing power capable to deal with it. In some ways, you’d struggled to write a better use case for cloud analytics.

The majority of data sources that businesses will use to feed predictive analytics are also cloud-based. Weblogs, operations data, customer service interactions, weather reports, and global markets are just some examples. Keeping it all cloud-based makes sense then. It also means that companies don’t have to rely on supplying their own hardware and servers to support intensive analytics programmes. Cloud resources mean they can have as much or as little as they need, and they can also change it on the fly. Basing predictive analytics in the cloud means it is no longer price-prohibitive for businesses of any size.

One of the significant benefits of predictive analytics is that it allows companies to see into the future and be pro-active rather than reactive. Comparing historical models to what is happening right now, allows these analyses to be more accurate and more relevant. So, feeding in real-time data is crucial. This is another great use case for cloud computing. If data is fed from one source to local storage, and then back to another source, it is no longer real-time. Basing it in the cloud prevents this.

Artificial Intelligence

Bringing AI and Machine Learning into analytics is nothing new. Use cases of AI are everywhere, and they’re common in the world of data analysis too. Automating tasks previously thought too complex and having analytics programmes that extrapolate insights for themselves are just two examples. Many sellers of cloud-based analytics platforms offer some form of AI or Machine Learning as standard with their solutions now, and the cloud is the right environment for it.

AI and Machine Learning share some similarities with predictive analytics that we have already discussed. They require a lot of data and they require a significant amount of processing power to perform their analysis. The algorithms and logic components used by AI are highly complex and powerful and require hardware to match. For most companies, purchasing, installing and maintaining this sort of hardware on-premises just isn’t possible on their budgets.

For a technology such as AI, which learns from data to improve its forecasting and analytical ability, having access to as much relevant data as possible can be significant. This is a critical factor in deciding to deploy your analytics in the cloud. We have discussed already how deployment in the cloud grants greater and easier access to data sources and the point still stands here. It makes good sense.

Predict the Future with Cloud Analytics

Cloud-based analytics make a lot of sense. You get all the benefits of cloud computing that you would from any other cloud-based software. The flexibility, the scalability and the accessibility rank top amongst those. But it also means you get to take advantage of the latest and best technology in the industry. As we have seen, predictive analytics and AI are simply suited better for running in the cloud. Furthermore, the cloud is where these technologies are designed, released and maintained – so why would you restrict yourself from that?

If you’d like to talk to one of our expert team about cloud-based analytics then get in touch today.