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> use read replicas for BI with a good visualization tool

Put up 2 or 3 read replicas, split your queries so writes happen to main and reads come from replicas (supported out of the box by many modern ORMs), and you can scale to millions in daily active users for most startup workloads.

Really the hard part of BI is that folks who need the info don’t wanna learn SQL. The ones who can do SQL, will struggle to keep up with your changing schema.



I give them Metabase. Metabase pointed to read-replica-3; and via Metabase API one can add lots of meta-data about tables and fields so the BI folk can point & click to build reports (and keep up with schema changes (which I mostly resolve with views anyway))


The hard part of BI is application developers not wanting to support a stable data model and changing the schema all the time, often made harder by BI people not knowing what they want and being stuck with a brittle integration.

Add analytics reporting views in your app database as the 'API' is the way.


> Really the hard part of BI is that folks who need the info don’t wanna learn SQL.

Data analysts are fine with SQL though. Every "get into data analysis as a career" course will teach you SQL (about 70% of what the querynomicon teaches [1]).

[1] https://github.com/gvwilson/sql-tutorial


> Data analysts are fine with SQL though.

Yes! I haven’t seen startups hiring these though. Somehow I always end up doing this as a side-gig on my engineering job.


Definitely - I've been surprised at some very complex pipelines built with pandas, etc. because someone didn't want to use SQL...




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