Data management professionals have long and sometimes rather Quixotically driven organizations to “get past the spreadsheet culture.” Maybe that’s misguided. The recent furor over a widely read social science paper may show how we can look to scientific peer review for a way to govern data, spreadsheets and all.
Recently, it was found that a key study underpinning debt-reduction as a driver of economic growth based its conclusions on a flawed spreadsheet. As this ArsTechnica article describes, Carmen Reinhart and Kenneth Rogoff’s Growth in a Time of Debt seemingly proved a connection between “high levels of debt and negative average economic growth”. But, per a recent study by Thomas Herndon, Michael Ash, and Robert Pollin, it turns out that the study’s conclusions drew from a Microsoft Excel formula mistake, questionable data exclusions, and non-standard weightings of base data. The ArsTechnica piece finds those conclusions fade to a more ambiguous outcome with errors and apparent biases corrected. Continue reading
As important as it is, data modeling has always had a geeky, faintly impractical tinge to some. I’ve seen application development projects proceed with a suboptimal, “good enough”, model. The resulting systems might otherwise be well-architected, but sometimes strange vulnerabilities emerge that track directly to data design flaws.