What is the similarity between stability and the S&P 500 index? How can we use data to identify fire risks and where to best open a coffee shop in New York City? 

From using regression to identify fire risks in New York City to managing complex process control, it all comes down to getting the right information to the right person at the right time to make a decision. Drew explains what stability means, and the tension between  machines and people as it pertains to data. 

Where within the chain of operation in an industrial company is the best place to insert a piece of software? Is a bus system just a bunch of big computers moving around on wheels? Does machine learning hold the answer to maximising the value of each interaction between humans and software? Are we all data engineers regardless of what our name card states?

Drew explains how to take heterogenous data streams and distill it into a stability score that is an index of operations and produce high value alerts. We also explore human machine interaction to build a model more effectively than a fully unsupervised method.

How to engage customers and speed up the sales process? How to get a sale out of a production plant fire? How should you price SaaS so that it encourages engagement and referrals? How to identify who isn’t pulling their weight on a power grid system?

Drew explains his sales philosophy and lessons learnt. We also explore a few case studies that makes use of Alluvium Primer to increase data processing and decision making speed from months to minutes.