Not everyone in your organization wants or even needs to be a machine learning engineer, at least right now. But that’s kind of the point of the data academy: it’s about up-skilling the staff you have to take the first steps in building a strong data culture. If you start to read my series of posts on building the data academy, you’ll see me repeat the claim that most organizations have more data talent than they know or use. This staff may have skills, opinions and ambitions in how to use data at your organization, but need the training and the buy-in to do it. These are the candidates who you want to enroll in your data academy, and this is what they might look like. From your underwhelmed data analyst, to your automation-anxious foreman, to your math-phobic operations manager, the analytics academy takes all kinds. But finding the right talent is just the beginning.

1. Building your data
academy: Identifying
students

2. Where the expectations gap is wide
• Analysts who were educated to analyze data but
instead clean it all day
• Keep your rising talent by bringing the bootcamp to
them

3. They know there’s a problem but…
• Not necessarily “data people,” but logical & savvy
• They are concerned & eager to future-proof
themselves
• Give them the resources to do it!

4. The analytics myth-busters
• Deep domain expertise, allegedly “math-phobic”
• Show them that analytics is way more than high
school math!
• Without strong domain knowledge, your academy
will fail

5. LET'S TALK
WEBSITE
stringfestanalytics.com
EMAIL ADDRESS
george@stringfestanalytics.com
LINKEDIN
linkedin.com/in/gjmount