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@OSPpatrick@DSMStrength What @OSPpatrick said with a side of pipelines/ingestion (which could be pre-processing) and communication (pinging others when things are available).
8) find integrations that support what you are doing, there are a ton of tools out there.
9) don’t be afraid to ask for help, there are so many ways to do the same thing. Just because it works doesn’t mean it’s the best way. Also, people have already done what you want to do
Things I have learned in building a complex DB to handle multi use case applications.
1) automation is your friend find ways to replicate repetitive work.
2) notes and documentation, while hard to do will save you time long run 1/2
6) don’t build everything that’s asked for, is it a real need or a need right now. Find a way to filter requests.
7) in parallel to building your automation build ways to update your current data. No data is perfect and corrections are always necessary (another tough lesson)
This is a very solid list for sure and I am positive any of them are happy to help, but likely dependent on what you are hoping to develop. Many things can be done with R/Shiny and also many different ways (ex. data.table vs tidyverse). So be specific in what you want to do.
Squirtacular 2023
Minnetonka Blue > Duluth (3-2)
#1 seed goes down in Squirt B. TONKA shocks Duluth! Jack Bosch (31 saves) named #LotzzaMotzza POTG.
@TenanATC Well, your argument was it doesn’t do this one thing so I saved you money (I.e you don’t need to buy it). Which suggest the only reason to buy it is to do the thing you say it can’t do.