Data Lake Swamps, Silent Failures: Anti-Patterns You Can Audit Before Migrating
Data lakes were supposed to be the answer to everything. Dump all your data in, worry about structure later. But a few years in, a lot of teams are staring at what looks less like a lake and more like a swamp—murky, tangled, and full of things you can't find or trust. I've seen it happen. A startup spends months building a data lake, only to realize nobody can query it without a guide. Or an enterprise migrates everything to the cloud, then watches storage costs balloon while data quality tanks. The fix isn't to abandon the idea. It's to audit your design before you move more data in. Who’s on the Hook for a Data Lake That Goes Bad? Ownership: data engineers, architects, or the business? The uncomfortable answer is that everyone has a slice, but no one holds the whole pie. Data engineers own the plumbing.