Bad Data Costs the U.S. $3 Trillion Per Year  — Tom Redman wrote this excellent article for HBR in 2016. This seminal piece may have seemed hard to comprehend in 2016, but if you can’t see it now, you aren’t looking. The article maintained the big data market back then totaled $136 billion per year. But IBM estimated the yearly cost of poor-quality data, in the US alone, reached an astonishing $3.1 trillion. This is why we built Inveniam IO.

Rodman wrote: “Such hidden “data factories” are expensive. Consider:

50% — the amount of time that knowledge workers waste in hidden data factories, hunting for data, finding, and correcting errors, and searching for confirmatory sources for data they don’t trust…Inveniam solves this

60% — the estimated fraction of time that data scientists spend cleaning and organizing data, according to CrowdFlower…Inveniam solves this

75% — an estimate of the fraction of total cost associated with hidden data factories in simple operations, based on two simple tools, the so-called Friday Afternoon Measurement and the “rule-of ten.”…Inveniam solves this

If you have data challenges, or price discovery problems, around data rich, low frequency trading assets let us help.

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