If you’re trying to solve data related problems with no or limited resources, be them time, money or skills don’t go no further. This talk points mostly to decades old technology, free operating systems and cheap hardware if possible, but if it makes sense to spend a hundred bucks instead of tearing your hair, I’ll say so.
This talk is opinionated. This talk is for the underdog. Talks on theory and awkward technology descriptions are abundant, deep learning is the craze, but when it comes to the daily grind of data people around the world the silence is deep. I'm trying to share tips and tricks and fully baked recipes - even a full data stack with open source code relying on good ol' seventies tech for durability.
I'm sure that you've all made your related decision the best you could for reasons you have, but if you can influence decisions still here are my two cents. This talk does not contain made up sample code and false promises of fancy technology. I talk about stuff we use in production. Period. It’s gonna be fine, but your mileage may vary.