We evaluated time-series databases and complementary services to stream-process sensor data. In this talk, our evaluation will be presented. The final implementation will be shown, alongside python-tools we’ve built and lessons learned during the process.

We talked about:

Ellen’s background Why Ellen switched from data science to data engineering The overlap between data science and data engineering Skills to learn and improve for data engineering Ways to pick up and improve skills (advice for making the transition) What makes a data engineering course “good” Languages to know for data engineering The easiest part of transitioning into data engineering The hardest part of transitioning into data engineering Common data engineering team distributions People who are both data scientists and data engineers Pet projects and other ways to pick up development skills Dealing with cloud processing costs (alerts, billing reports, trial periods) Advice for getting into entry level positions Which cloud platform should data engineers learn?

Links:

Twitter: https://twitter.com/ellen_koenig LinkedIn: https://www.linkedin.com/in/ellenkoenig/

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