Machine learning risks are real. Do you know what they are? 

Machine Learning Risks are real and can be very dangerous if not managed / mitigated. Everyone wants to ‘do’ machine learning and lots of people are talking about it, blogging about it and selling services and products to help with it. I get it…machine learning can bring a lot of value to an organization – […]

What is the cost of bad data?

How much is bad data costing you? It could be very little – or it could be a great deal. In this article I give an example of what the cost of bad data really is. A few days ago, I received a nice, well designed sales/marketing piece in the mail yesterday. In it, a […]

What can you DO with Machine Learning?

Everyone’s talking about machine learning (ML) and Artificial Intelligence (AI) these days.  If you are a CxO or work in IT or marketing, I’d bet that you hear these terms more than you probably want to. It feels an awful lot like the early data of Big Data or Business Intelligence or the days when […]

Beware the Models

“But….all of our models have accuracies above 90%…our system should be working perfectly!” Those were the words spoken by the CEO of a mid-sized manufacturing company. These comments were made during a conversation about their various forecasting models and the poor performance of those models. This CEO had spent about a million dollars over the […]

Big Data Roadmap – A roadmap for success with big data

I’m regularly asked about how to get started with big data. My response is always the same: I give them my big data roadmap for success.  Most organizations want to jump in a do something ‘cool’ with big data. They want to do a project that brings in new revenue or adds some new / […]

Are your machine learning models good enough?

Imagine you’re the CEO of XYZ Widget company.  Your Chief Marketing Officer (CMO),  Chief Data Officer (CDO) and Chief Operations Officer (COO) just finished their quarterly presentations and were highlighting the success from the various machine learning projects that have been in the works. After the presentations were complete, you begin to wonder – ‘are […]

2017: A year in review (and a preview of 2018)

2017 was an interesting year for me. I bought a new house in February after being homeless for about 4 months. In October 2016, my wife and I sold our house and spent the 2.5 months of 2016 and the first 1.5 months of 2017 traveling around the Southwest (we spent the time in Colorado […]

Deep learning – when should it be used?

“When should I use deep learning?” I get asked that question constantly. The answer to this question is both complicated and simplistic at the same time. The answer I usually give us something along the lines of ‘if you a lot of data and an interesting / challenging problem, then you should try out deep […]

When it comes to big data, think these three words: analyze; contextualize; internalize

If you don’t know, I’m a bit of a data nerd.  I’ve been writing about big data, data science, machine learning and other ‘new’ stuff for years.  I believe in data science and I believe in big data. I’m a fan of machine learning (but think you probably don’t need it) for the majority of […]

Data and Culture go hand in hand

A few weeks ago, I spent an afternoon talking to the CEO of a mid-sized services company.  He’s interested in ‘big data’ and is interviewing consultants / companies to help his organization ‘take advantage of their data’.  In preparation for this meeting, I had spent the previous weeks talking to various managers throughout the company […]