The Dirty Secret of Data Quality

Most enterprise AI projects fail not because of the model, but because of the data underneath.

A hallucination everyone recognizes as a hallucination is manageable. A hallucination that looks like a quarterly forecast is a different category of problem.

Common failure modes: the same metric calculated differently across systems and regions; data that records what happened but not why; pipelines that appear to be running while feeding last quarter's reality into today's decisions.

The model is the last mile. Data quality is the road.

  • Beige Bananas — Data & AI, Built with Love
  • Our Services
  • Strategy & Advisory
  • Data Engineering
  • AI & Machine Learning
  • Operationalize
  • AI consulting services that ship to production, not pilots
  • Data engineering services built for AI workloads
  • Data strategy consulting that ends in a build plan
  • GBS innovation: from service organization to intelligent operating system
  • Industries we focus on
  • Media & Entertainment
  • Consumer Packaged Goods
  • Retail & D2C
  • Insurance
  • Use Cases & Insights
  • Modern BI is Broken
  • Cultural Capital
  • Everywhere and Nowhere
  • The Squeeze
  • Beyond the Prompt: Agentic AI
  • RAG to Riches
  • Careers at Beige Bananas
  • Talk to us
  • Time Warp