My Nine “Truths” of Data Analysis

Posted on June 06, 2011

For over 20 years, viagra I’ve been a data coach for hundreds of teachers, generic first as a top-level official in two Maryland school districts and now on the faculty of a university leadership center. I’ve had mountain-top experiences with school teams whose members really get what it means to use data to inform their instruction, visit this site and I’ve led sessions that were disasters.

Over the years, I have accumulated a set of what I first called “My Ten Commandments of Data Analysis.” Then, I reconsidered one, and “nine commandments” just didn’t sound right. So I now call them “My Nine Truths of Data Analysis.” They are not necessarily the truths, but they are definitely my truths. I would be interested in how they compare with the thoughts and experiences of others.

My first truth. We don’t need “data driven” schools. We desperately need “knowledge driven” schools. There is a big difference. Data are ways of expressing ideas, such as in numbers, sounds, and images, and they have very little value and usefulness in and of themselves. Data are merely the building blocks of the information age.

Data are useless unless they are first organized into meaningful patterns called information. This transformation is, largely, a technical process of summarizing and putting the numbers into usable forms like charts and graphs. Schools are acquiring some skill at this, and commercially developed instructional-management systems (or data warehouses) are facilitating this process. But many schools are still drowning in data and information.

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AuthorRonald S. Thomas, Edweek