I was interviewed by IBM to share my thoughts on a topic related to data science about which I’m passionate: How do we know what we know and, once we know it, how do we know it’s the truth? IBM turned that interview into a comic strip (see below) and I summarize my points in this […]
The practice of data science requires the use of analytics tools, technologies and languages to help data professionals extract insights and value from data. A recent survey by Kaggle revealed that data professionals relied on Python, R and SQL more than other tools in 2017. Looking ahead to 2018, the survey results showed that data […]
![Measure-Customer-Feedback-Chart-2[1]](https://businessoverbroadway.com/wp-content/uploads/2016/05/Measure-Customer-Feedback-Chart-21-100x100.png "Three Problems with Customer Surveys and How to Fix Them")
Customer surveys are the foundation of many CX programs. Improvements in the content of these surveys, however, have not changed for decades. Businesses now have a plethora of data sources to help them understand their customers. The use of these Big Data sources will necessarily impact the type of questions you need to ask in […]
We live in a Big Data world, one in which everything is quantified. As a result, customer-centric professional (e.g., customer experience, customer success) are increasingly using the practice of data science to extract value from these data. As the field of data science evolves, more terms are being used to define the process by which […]
I am preparing to launch a data science survey in the next couple of weeks. This study will be help verify the findings from a similar study I conducted two years ago (see Investigating Data Scientists, Their Skills and Team Makeup) as well as help me explore additional topics of interest (e.g., satisfaction with data […]
A while back, I wrote about the three skills needed to practice data science. Based on a factor analysis of many different skills, data science skills fall into three broad skill areas. These skill areas are: 1) subject matter expertise, 2) technology/programming and 3) statistics/math. Data science is essentially a way to extract insight from data using […]
Each year, I write a summary of my most popular blog posts. This year-end summary is a rather simple exercise. I count the pageviews of my blog posts and present the top 10 posts of the year. This year’s BOB blog count, however, only goes from January through June 2016. Since June, I have been writing primarily […]
Data scientists have a variety of different skills that they bring to bear on Big Data projects. These skills cut across Subject Matter Expertise, Technology, Programming, Math & Modeling and Statistics. One valuable skill that is becoming popular in data science is machine learning. Machine learning is a method of data analysis that automates model building […]
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