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Everything We Wish We'd Known About Building Data Products - First Round Review
Quote: "Where to Start Building: A lot of people choose to start building by modeling the product in question. Some start with feature discovery or feature engineering. Others start with building the infrastructure to serve results at scale. But for Belkin, there's only one right answer and starting point for a data product: Understanding how will you evaluate performance and building evaluation tools.
“Every single company I've worked at and talked to has the same problem without a single exception so far — poor data quality, especially tracking data,” he says.“Either there's incomplete data, missing tracking data, duplicative tracking data.” To solve this problem, you must invest a ton of time and energy monitoring data quality. You need to monitor and alert as carefully as you monitor site SLAs. You need to treat data quality bugs as more than a first priority. Don’t be afraid to fail a deploy if you detect data quality issues."
assessments_&_evaluations  control_systems  dashboards  data_quality  economies_of_scale  instrumentation_monitoring  testing  tracking  information  infrastructure  via:ajohnson1200  massive_data_sets 
september 2015 by jerryking
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