Full-stack analytics… is that made up?
Maybe?
Though, I am not the originator! The first time I heard of the term I was at an Adobe conference, where I came across Frederik Werner’s Full Stack Analyst Blog.
It is a generous title that I have adopted in recent times to help communicate all of the things that I can do with data.
Some days, it means that I am a Digital Analyst pitching the value of analyzing customer fallthrough and retention in Adobe Analytics to my Product Manager.
Other days, it means that I am a Data Analyst writing SQL to query POS transaction data from the on-premises data warehouse, and running an affinity analysis in R.
Still, on other days, I am a Data Engineer & BI Developer writing API GET requests in R or Python and creating data pipelines to be ingested and transformed into an insight-rich and user-friendly PowerBI Dashboard.
And finally on whatever days that are left, I become a Data Scientist that attempts to classify unstructured text data using a mixed membership approach to topic modeling in R.
These are all the things that I have become over the years to be able to answer the problems that I find most interesting.
Full Stack Analyst / Full Stack Analyst
All jokes aside, I believe that a full-stack analyst is someone who is curious by nature and loves to apply their diverse assortment of analytical skills and techniques to solve valuable problems.
That, or a generally informed and indecisive person as it relates to careers within data & analytics.
