Strata + Hadoop World 2016 is happening next week, between December 5th and 8th in Singapore. I’m excited to be presenting at the conference on the subject of time series analysis for sensor data. More about my talk here. One of my key focus areas during the last several months at The Data Team, where […]Read more "Onward to Strata+Hadoop World 2016, Singapore!"
One of the changes envisioned in the big data space is that there is the need to receive data that isn’t so much big in volume, as big in relevance. Perhaps this is a crucial distinction to make. Here, we examine business manifestations of relevant data, as opposed to just large volumes of data. What Managers Want From […]Read more "Big Data: Size and Velocity"
Introduction Effective measurement is as important in the data science revolution as effective analysis is. Without data that is measured correctly, we fly blind into data analysis, and such a scenario can hardly be effective at extracting insight from the data we possess. In this post, I discuss some challenges facing effective measurement in the […]Read more "Challenges of Effective Measurement"
As a data science consultant that routinely deals with large companies and their data analysis, data science and machine learning challenges, I have come to understand one key element of the data scientist’s skill set that isn’t oft-discussed in data science circles online. In this post I hope to elucidate on the importance of domain […]Read more "Domain: The Missing Element in Data Science"
Data products are one inevitable result and culmination of the information age. With enough information to process, and with enough data to build massively validated mathematical models like never before, the natural urge is to take a shot at solving some of the world’s problems that depend on data. Data Product Maturity There are some […]Read more "Insights about Data Products"
This may sound weird, but one sure way to not have perspective about the business in an innovative and constantly changing industry is to bury yourself within regular work. This is the meaning of the title – which comes from a book of the same name. By regular work, I mean work in which you […]Read more "Data Perspectives: “Orbiting The Giant Hairball”"
Being data-driven in organizations is a bigger challenge than it is made out to be. For managers to suspend judgement and make decisions that are informed by facts and data is hard, even in this age of Big Data. I was spurred by a set of tweets I posted, to think through this subject. Decision […]Read more "“Small Data”and Being Data-Driven"