Most Important Skills For A Data Insights Executive At An Entertainment Talent Agency
Suzi, an Executive of Data Insights at an entertainment talent agency, emphasizes a passion for entertainment as a crucial, "untaught skill," alongside strong data analysis capabilities. The ability to "cipher through data" and extract key insights to tell a compelling story is vital for success in this role, requiring experience with various data sources and tools.
Data Analysis, Entertainment Industry, Passion, Storytelling, Data Visualization
Advizer Information
Name
Job Title
Company
Undergrad
Grad Programs
Majors
Industries
Job Functions
Traits
Suzi Stein
Executive, Data Insights
Entertainment Talent Agency
Amherst College, 2014
Currently pursuing MBA at UCLA Anderson as part of their FEMBA program
Environmental & Related Sciences
Arts, Entertainment & Media
Data and Analytics
Student Athlete
Video Highlights
1. Passion for entertainment is crucial, as it provides context and understanding of industry trends.
2. Strong data analysis skills are essential, including the ability to interpret data and extract key insights.
3. Experience working with various data sets and tools is vital for success in an entry-level data analyst role.
Transcript
What skills are most important for a job like yours?
Being in entertainment, the biggest thing is honestly being passionate about it. We're working with a lot of clients from different areas of entertainment. To thrive in our job, we have to be in the know about what's going on.
This includes content and music being released, or even trends in the industry. That can be different companies merging or new platforms emerging. People who are really passionate about entertainment have a helpful context and a skill that can't be taught.
In terms of hard skills, to be a data analyst, you have to be willing to dive deep into data. You need to understand the storytelling you want to tell through data insights. Being able to sift through data and really understand the key insights to take away is important.
Having experience sorting through different data sets and pulling data from UIs or different tools is critical. This allows you to hit the ground running in an entry-level position within data.