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Dec 2022 How to fuel innovation with agile data governance

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Thriving data cultures prioritize inclusion, collaboration, and transparency over command and control. They work iteratively vs. trying to "boil the ocean." But of course, this is easier said than done, right? 

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A data analyst, scientist, and engineer walk into a bar...w/ Danielle Oberdier

About this episode

Quick, what’s the difference between a data engineer and a data analyst? One preps the data, the other analyzes the data, right? A data scientist, meanwhile, analyzes more complex and disorganized data. The truth is all three of these roles perform overlapping functions leading to an incredible amount of confusion in the job market.    

Join Tim, Juan and special guest Danielle Oberdier, founder of DiKayo Data and host of the popular DataFemme podcast, to talk about the state of data jobs. How do we make sense of the roles that are out there today, who should companies be looking for in their hiring process, and what new and exciting data positions are starting to emerge?

This episode features
  • Certifications that make you more marketable

  • How to stand among your peers in a crowded job market

  • What was the very first job you ever had?

Key takeaways
  • Data scientist vs. data analyst vs. data engineer

  • Google is your friend -- always be learning, grab those libraries, follow the patterns, etc.

  • Certifications and networking will set you apart in the job market.

Mentioned in this episode

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Special Guests

Avatar of Danielle Oberdier
Danielle Oberdier Founder, Dikayo Data