Tejus Parikh

I'm the CTO and co-founder of WideAngle and I write weekly about building startups and the technology that powers them from Atlanta, GA, the startup capital of the south. Follow me on twitter or subscribe to stay in touch.

Five Data Model Mistakes Common to Startups

Posted on May 9, 2017

Hyperfocus on the first customers and the MVP can often lead to these five common datamodeling mistakes

Hyperfocus on the first customers and the MVP can often lead to these five common datamodeling mistakes

It's not surprising to come across a floundering B2B startup in the process of a significant code rewrite. New features to attract customers would appear to be the logical approach in such times, but new features may be nearly impossible to build because of basic data-model mistakes made early in the life of the company. Most developers are familiar with the convention that a bug in production is more costly than a bug in development. Likewise, poor data structures behind production data can be crippling in critical situations.

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