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How I Used a Machine Learning Model to Generate Actionable Insights

Combining data science with data analytics

Analytic functions are divided into data science vs. data analytics. Rarely is there mention of combining both together. Today I’d like to share how I used a machine learning model for a data analysis and my approach to translate model results into actionable insights.

A couple years into my first data analyst role, I felt I had worked on all the possible projects I could supporting marketing and was no longer learning anything new. I started looking for another data analyst job and one of the companies I interviewed with wanted me to complete a take home assignment before I could move to the next phase of the interview process.

I was sent a raw file containing relevant movie data with an assignment stating “An executive producer at a movie studio has given you this dataset, and wants you to give a brief overview of an interesting insight derived from it that will help the studio’s business.”

Having a unique background as a data scientist turned data analyst I realized I could leverage a machine learning model to get the results faster and show the hiring manager my unique approach to this problem.

Why use a machine learning model instead of looking at the data like a typical data analyst would?

These are the steps I took to approach this assignment.

As a data analyst every time I get a request, I find it’s helpful to put myself in the shoes of the stakeholder to understand what they’re thinking.

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