Which Analyst Are You? - Issue 262

Data analyst career guide: an overview of roles, skills, and industry trends

Welcome to the Data Analysis Journal, a weekly newsletter about data science and analytics.

Hello from the Databricks Summit!

If you’re in town, let’s meet up and discuss - how did Databricks, a big data analysis platform, end up becoming yet another data warehouse? (As if we didn’t already have enough SQL databases.)

Today, I want to continue the conversation on differentiating yourself in analytics and explore the different types of analyst roles to help you figure out where you fit best.

I often tell analysts: Find your superpower and lean into it. Some are exceptional at math and analysis precision, and others shine in storytelling. Some have strong product thinking and design intuition, while others are faster with data acquisition. Yes, we should all be skilled at doing it all, but each of us has our own superpowers, unique strengths, and preferences. I hope this publication helps you identify yours and choose the flavor of analytics that fits you best.

Every domain becomes specialized.

Specialization is happening across every field. For example, Product Managers are now often categorized into 4 main archetypes:

The Growing Specialization of Product Management

Or 3 archetypes. Or 7 archetypes. Depending on whom you ask. Each archetype comes with its own focus, skill set, tools, and deliverables. It’s believed that someone suited for one archetype may not thrive in another, even within the same role.

Data engineering is undergoing a similar evolution: