Poor data quality costs organizations at least $12.9 million a year on average, according to Gartner. Most teams trace it to the same root cause, which is analysts building on the wrong data because they had no reliable way to find the right data. A financial analyst joins a new team, opens Microsoft Fabric, and sees 340 tables across 12 workspaces
Most enterprise AI agents hit a ceiling within months of going live. The model stays the same, the prompt gets longer, and the team spends more time patching the system than the system saves them. It is a context problem. Static instructions cannot absorb what an agent learns from thousands of real-world tasks, so performance stays flat and maintenance costs
Most enterprises did not arrive at their cloud bill by choosing it. They moved workloads over, added services, and watched the monthly invoice climb without a clear picture of why. The structure underneath was never designed for the cloud, only copied into it. That gap between moving to the cloud and building for it is where the money leaks. Companies
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