A simple explanation of machine learning (ML). You don't need a Phd or even a degree to use ML, just use it.

Digital disruption is much more than an abstract concept promoted by analysts and vendors; it is now a reality for most organizations.

More than one-third of executives in a recent Forbes Insights/Treasure Data survey say they are being directly affected by competition from digital and data-savvy players in their markets.

What does it take to embark on a data-driven disruption journey? Here are some ways to get started:

1. Creating new markets or leveraging the power of information to offer solutions in new ways.

2. Be the disruptor.
The best way to fend off disruptors is to become the disruptor. Shift their business models using data-driven products and services, or by linking up with digital-savvy players.

3. Surface your data assets.
With the influx of data that an increasingly digital world creates about customers, access to clearly organized, consolidated data is crucial. Think of ways to create entirely new products or services through new channels.

The most likely form of disruption is through the actual monetizing of information technology.

​The disruption that is radically reshaping today’s markets, as well as creating new ones, is driven by data, with the goal of enriching the customer experience, and delivering goods and services on demand without so much as a hiccup in supply chains or response systems. To accomplish this, data needs to move fast, seamlessly and be accessible.

As Holger Hürtgen and Niko Mohr, of McKinsey, recently put it:

Those organizations leading the way and digitally disrupting their markets have learned to employ customer data in new and innovative ways not simply to be disruptors, but to provide superior customer experiences.

​Source: Forbes Insights (click on image to read more)

This is a rather interesting article by Jeroen ter Heerdt.

"Data Science is dead. It is quickly getting replaced by stuff great data scientists built. Every big cloud vendor is doing it. Need to do a churn analysis? Done. Need to predict energy efficiency? Done. Want a recommendation engine? Done. Need to process genders, age and emotion from images? Done. From video? Done. Need to recognize certain logo's in images? Done. Need to understand sentiment? Done. Need to translate text or summarize text? Done.

What do you need to use these solutions? Just programming skills. Being able to talk to a REST API, that is all you need. Any programmer can do this. Behind this REST API is a algorithm built by the best and brightest of data scientists in the world that made themselves (and their fellow data scientists) obsolete".

​You can join the "debate" here.