3 Ways to Use AI for Analytics Engineering
How it can speed up your workflow without sacrificing quality
Lately, I’ve been exploring how AI can save me time in my work as an analytics engineer. While I’ve been quite reluctant to have it write complex data models for me, I’ve found many uses for it that don’t involve solving my most challenging problems.
In fact, I think AI is best used for the simple stuff!
These are the things that are:
a) redundant
b) simple with no room for further learning
c) time-consuming to find answers to, but not necessarily to learn
In today’s newsletter, I’ll share three use cases (with prompts) I’ve recently used with Claude to help me get what I need, fast, freeing up more time to focus on solving more complex problems.
To explain design decisions
AI is great at explaining why code is written a certain way. It pulls from documentation on whatever language, warehouse, or tool you are using, preventing you from needing to scour through it to find an answer.
I’ve found it useful in understanding:
specific functions
tradeoffs in design
outputted field values
