Why advanced analytics needs the cloud

The cloud makes it easier to launch enterprise-scale machine learning, but the variety of options can be confusing.

Most industries are using intelligent machines to discover something new and do something better than human beings are doing it now. In energy and technology, algorithms are anticipating driver behaviors that could lead to loss and predict the degraded performance of the power infrastructure. Intelligent machines are extending healthcare beyond the walls of the hospital by using environmental factors (such as ozone levels) to predict spikes in emergency-room visits.  There are even digital worlds that simulate and predict flaws, cost and performance in manufacturing.

Figure 1: If you combine the power and flexibility of the cloud with a strong Analytics IQ, you can add intelligence to just about any part of your business. Click to expand.

The power of machine learning grows as more data becomes available. And we are producing new data at an astounding rate. It is entirely possible that within the next 3 years every human being on the planet will create about 1.7 megabytes of new information every second.

But we are far from putting this data to good use. By some analyst estimates, we may be capturing only 20%-30% of the value of our manufacturing data, 10%-20% of the value of our public-sector data, and 10%-20% of the value of our healthcare data.

In every industry, the barriers to capturing the full value of the data we create is nearly the same. Data is locked away in silos. Getting a machine to spot meaningful insights typically takes a lot of processing power and data storage capacity. The enterprise is yet to be shown a convincing demonstration of the data’s potential.

These are all challenges that can be met with a strong Analytics IQ and the proper deployment of hybrid cloud technology. The cloud is the fastest and least expensive way to integrate data. The cloud brings sophisticated algorithms, fast computing platforms and massive storage capacity within reach. It lowers the barrier to adoption and makes it easier for enterprises to get their feet wet with inexpensive experiments. Cloud services make it easier to build compelling applications quickly by delivering in small, meaningful chunks.

Figure 2: How to use the cloud to build a smarter enterprise. Click to expand.

Intelligent machines are becoming a ubiquitous and essential part of business operations. Algorithms trained by faster, smarter data now play a key role in enterprise transformation. Hybrid clouds are emerging as the future platform for the intelligent enterprise.


Jerry Overton is a Data Scientist and Senior Principal in DXC’s Analytics group. He leads the strategy and development for DXCs Advanced Analytics, Artificial Intelligence and Internet of Things offerings.

Jerry is the author of the O’Reilly Media eBook “Going Pro in Data Science: What It Takes to Succeed as a Professional Data Scientist.” He teaches the Safari Live Online training course “Data Science at Enterprise Scale.” This post is a companion to Jerry’s upcoming talk at a Strata + Hadoop World event, where he will give an executive briefing on why advanced analytics needs the cloud.

RELATED LINKS

Moving from data capture to data analytics

From lakes to watersheds: A better approach to data management

2017: Bigger, faster data makes for smarter machines

 

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