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The goal of this newsletter is to promote continuous learning for data science and engineering professionals. To achieve this goal, I’ll be sharing articles across various sources that I found interesting. The following 5 articles made the cut for today’s newsletter.

1. Architecture for Telemetry data

A good reminder that the software development architecture can be significantly simplified for capturing telemetry data here

2. 5 popular job titles for data engineers

This post here lists 5 popular job titles: data engineer, data architect, data warehouse engineer — I think Analytics engineer is missing in that list but a good post nonetheless. I hope that we get some consolidation and standardization of these job titles over the next few cycles.

3. [Podcast] startup growth strategy and building Gojek data team – Crystal Widjaja

Really good podcast, highly recommended! here

4. Tenets for data cleaning

A must-read technical whitepaper from legendary Hadley Wickham. These principles form the foundation on top of which R software gained a lot of momentum for adoption. Python community uses similar tenets. Must read! here and here

5. Magic metrics that startup probably as product/market fit from Andrew Chen

A must-follow Growth leader!

1. Cohort Retention curves flatten (stickiness)
2. Actives/Reg > 25% (validates TAM)
3. power user curve showing a smile

Magic metrics indicating a startup probably has product/market fit:

1) cohort retention curves that flatten (stickiness)
2) actives/reg > 25% (validates TAM)
3) power user curve showing a smile — with a big concentration of engaged users (you grow out from this strong core)

— Andrew Chen (@andrewchen) October 15, 2019

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Thanks for reading! Now it’s your turn: Which article did you love the most and why?