Conversation

Feel very foolish: I've been doing data analysis and viz for Quantum Country "in the cloud" using BigQuery for the past few years, because it's what I was used to from KA. Big data! But we only have a few M samples. I can fit it all in RAM! I'm *so* much faster iterating locally.
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This is my first time using an R notebook for something serious, and it is certainly quite a powerful tool for thought. Visualizations which would have taken me a day to finagle in BQ/GDS now take me a few minutes. This makes me ask/answer different questions…
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My analysis workflows usually go the other way around - python in a local notebook first, sql in a data warehouse later. Even if the data is too big for local machine, it pays to take random samples at first and play with them with a pandas or dplyr type api!
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