Jim Harris is a recognized data quality thought leader with 25 years of enterprise data management industry experience. Jim is an independent consultant, speaker, and freelance writer. Jim is the Blogger-in-Chief at Obsessive-Compulsive Data Quality, an independent blog offering a vendor-neutral perspective on data quality and its related disciplines, including data governance, master data management, and business intelligence.
Data. Our industry really loves that word, making it seem like the whole world revolves around it. We certainly enjoy revolving a lot of words around it. We put words like master, big, and meta before it, and words like management, quality, and governance after it. This spins out disciplines
Data stewardship is one of the most important, and commonly misunderstood, aspects of data quality and data governance. Not only are the characteristics of a good data steward a rare combination of skills to find in an individual employee, the culture of most organizations does not nurture the development of data stewardship. It would not
Truth is a funny thing. And I don’t just mean how some true things are funny. A few examples include that strawberries are not berries, peanuts are not nuts, Chock Full o’Nuts coffee does not contain nuts, and the singer-songwriter Barry Manilow did not write his hit song “I Write
Henrik Liliendahl Sørensen recently blogged about the times when a HiPPO (Highest Paid Person’s Opinion) outweighs data in business decision-making. While I have seen plenty of hefty opinions trump high-quality data, those opinions did not always come from the highest paid person. The stubborn truth is that we all hold our
In my previous post, I used the book Mastermind: How to Think Like Sherlock Holmes by Maria Konnikova to explain how additional information can make us overconfident even when it doesn’t add to our knowledge in a significant way. Knowing this can help us determine how much data our decisions need to be driven
In her book Mastermind: How to Think Like Sherlock Holmes, Maria Konnikova discussed four sets of circumstances that tend to make us overconfident: Familiarity — When we are dealing with familiar tasks, we feel somehow safer, thinking that we don't have the same need for caution as we would when trying something
A panel discussion at the recent International Data Quality Summit opened with the seemingly straightforward request by the moderator for the panelists to begin by defining data quality. The resulting debate was blogged about by Ronald Damhof, who was one of the panelists. On one side of the debate was the ISO 8000 definition of data
“Correlation does not imply causation” is a saying commonly heard in science and statistics emphasizing that a correlation between two variables does not necessarily imply that one variable causes the other. One example of this is the relationship between rain and umbrellas. People buy more umbrellas when it rains. This
Yesterday was one of the two times a year that an equinox occurs. From its Latin roots, the term equinox translates as equal night since, on the day of an equinox, daytime and night are of approximately equal duration. This occurs because during an equinox the Sun is aligned with the center of the
My previous post pondered the term disestimation, coined by Charles Seife in his book Proofiness: How You’re Being Fooled by the Numbers to warn us about understating or ignoring the uncertainties surrounding a number, mistaking it for a fact instead of the error-prone estimate that it really is. Sometimes this fact appears to
