From 0 To Data Solution In 5 Phases To Land Contracts & Wow Bosses

Demystifying data infrastructure design, implementation and maintenance for short and long-term employees and new grads.

Zach Quinn
Pipeline: Your Data Engineering Resource

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In my mind, no data solution that begins with code doesn’t end in frustration or, at best, an overhaul six-ish months down the road. As I’ve gained proficiency, expertise and speed with conceiving, developing and implementing data solutions at varying scales, I’ve had few opportunities to develop from scratch — until I built my own reporting infrastructure.

In a jet-lagged (I had just flown from France) conversation with a fellow data professional seeking advice on building a data analytics solution I half-ranted, half-outlined steps I consider essential to building a data solution that isn’t just ready for use, but also one that is sustainable as it scales.

Perhaps I listened to myself talk for too long, but I believe there’s value to sharing the exchange with a wider audience. If only for the reason of keeping this train of thought coherently on the tracks.

The phases I present were gleaned through lessons, mistakes and observations at work and in my own tinkering. While they don’t necessarily represent a comprehensive roadmap to implementing a data warehouse-based solution…

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