5 Data Management Horror Stories to Avoid

The transition to data in motion requires a mindset shift toward building continuous data operations capabilities that are in tune with the time-sensitive, dynamic nature of today’s data.

It’s alive. Your data is your lifeblood, and like Dorian Gray’s painting, it’s doesn’t age well. You’ve got to move fast to put it to use or it will mold and decay right before your eyes.

Big data is the nightmare that ETL processes can’t wake up from. The data sources emerge from the depths of despair, and you can’t control them. Your ETL breaks as the data structure and schema drifts and shifts.

Has your data lake become a swamp, full of old tires and rusted cars? Did you just dump anything and everything into it without realizing the gruesome spawn you were creating? How will you ever get insights from this fetid swamp?

It started with one simple dataflow that scaled up and grew out and connected with others until you were left with an mess that is always on the verge of collapse. Now you spend your days like the walking dead heading from fire to fire trying to keep everything running.

I saw it, I swear. It was right there, those new fields that I know we collect, but I can’t find them anywhere in my data store. And it’s personally identifiable information for goodness sake. How will we survive the audit if it goes to some forbidden place!?