The following is an interview by Jeff Saltz with Jelle de Jong. Jelle, a certified DSPA Team Lead, is an independent consultant. He currently works with Lely, an agricultural business based in the Netherlands. Jeff: Can you provide some background on your consulting business? Jelle: I’ve been in the quantitative modeling industry for 15+ years. […]
The rapid increase in the number of data science projects and teams is driving an increasing need for data science management. To address this gap, it is tempting to think that any project manager (from a different field) could do the job. Or that a good senior data scientist would naturally be a good data […]
The following is an interview by Jeff Saltz with Hector Rangel. Hector, a certified DSPA Team Lead, is a Consultant and Data Science lead at Arena Analytics, a small consulting company located in Mexico. Jeff: Can you tell me a bit about yourself? Hector: I’m an industrial engineer and a business professional with 8 years of […]
The following is an interview by Jeff Saltz with Dr Thibaut Jombart (who is a certified DSPA Team Lead). Thibaut is an Associate Professor in Outbreak Analytics at the London School of Hygiene and Tropical / Imperial College London (LSHTM / ICL) He is also a Senior Data Scientist for the World Health Organization (WHO). […]
The importance of AI project management, or more specifically, managing AI projects, is highlighted by a survey showing that 85% of AI projects do not deliver on their promises to business. In other words, as noted by Forbes, most AI projects fail. An AI project is different than a typical software development project, and hence, […]
As organizations continue to expand their data analysis competencies, the data science function is becoming more of a team sport with numerous team roles within the data science group. Of all these roles, the difference between the data analyst and data scientist role is perhaps the most confusing. Indeed, the roles have similar responsibilities. Data […]
This post will explore managing analytics projects by focusing on three questions: What is the difference between a data scientist and a data analyst? What is the difference between analytics projects and data science projects? What project management / project coordination framework might be helpful to manage analytics projects? Project Management Training for Data Analytics […]
It’s an understatement that great leadership is challenging and rare. And leading data science teams has unique challenges: Stakeholders might get disillusioned by your team’s inability to deliver magic The battle to recruit and retain data science talent is fierce Data science’s ethical dilemmas are particularly perplexing There is not an agreed-upon process for managing […]
Data Science vs Software Engineering isn’t really a battle. Rather these are two somewhat overlapping and complementary fields that are similar in many ways. However, dig deeper in the discussion of data science vs software engineering, and you’ll find key differences in the two fields: Data science is more exploratory. Software engineers are more focused […]
While there is no standard process for a team to use when working on a data science project, CRISP-DM (CRoss-Industry Standard Process for Data Mining) is one framework that is often considered for data science projects. Perhaps because of this, there are lots of web sites describing the 6 phases of a CRISP-DM project, and […]
