VettedGaps has researched 19 problems people raise in r/dataengineering, each backed by real posts.
By category
Analytics & Reporting: 4
Performance & Reliability: 4
Automation & Workflows: 3
Integrations & API: 3
Top problems
Data engineers build AI chatbots that produce unreliable metrics(Automation & Workflows · 3 pieces of evidence)
Data engineers find AI-generated SQL unreliable for complex queries(Billing & Pricing · 5 pieces of evidence)
dbt engineers waste time manually QAing AI-generated code and tests(Automation & Workflows · 2 pieces of evidence)
What people say
“Guess what, the agents will calculate the metrics wrong occasionally, so as to giving wrong numbers. That won’t work. Instead, we have to define every metric as a function, and let LLM compose those functions to get some final resulting metric. How is this AI driven? It’s enti...”
From r/dataengineering, on “Data engineers build AI chatbots that produce unreliable metrics”
Read all 19
All 19 with evidence, competitors and paid demand are in VettedGaps PRO.