Datagraphy or Datalogy?

What is the study of data management best practices?

Do data management professionals study Datagraphy, or Datalogy?

A few of the things that a data management professional studies and applies are
  • Tools
    • Data Modeling tools
    • ETL tools
    • Database Management tools
  • Procedures 
    • Bus Matrix development
    • User session facilitation
    • Project feedback and tracking
  • Methodologies 
    • Data Normalization
    • Dimensional Modeling
    • Data Architecture approaches

These, among many others, are applied to the needs of the business. Our application of these best practices make our enterprises more successful.

What should be the suffix of the word that sums up our body of knowledge?

Both "-graphy" and "logy" make sense, but let's look at these suffixes and their meaning.


The wiki page for "-graphy"  says: -graphy is the study, art, practice or occupation of... 

The dictionary entry for "-graphy" says -"a process or form of drawing, writing, representing, recording, describing, etc., or an art or science concerned with such a process"


The wiki page for  "-logy"  says -logy is the study of ( a subject or body of knowledge).

The dictionary entry for  "-logy" says: a combining form used in the names of sciences or bodies of knowledge. 


The key word that we all focus on is data. 

In a previous blog entry, I wrote a review of the DAMA-DMBOK  which is the Data Management Association Data Management Body Of Knowledge. 

Data Management professionals study and contribute to this body of knowledge. As a data guy, I am inclined to study to works of those who have gone before. I want to both learn from their successes and avoid solutions that have been unsuccessful. 

Some of the writings I study are by people like:  Dan LinstedtLen Silverston, Bill Inmon, Ralph Kimball, Karen Lopez, William Mcknight and many others. 

I have seen first hand what happens to a project when expertise from the body of knowledge produced by these professionals has been discarded. It is not pretty. 

Why do I study these particular authors? These folks share their experiences. When I face an intricate problem, I research some of their writings to see what they have done. Some tidbit of expertise they have written about has shed light on many problem I have faced, helping me to find the solution that much sooner.

When I follow their expertise my solutions may still be unique, but the solutions fit into patterns that have already been faced. I am standing on the shoulders of giants when I heed their advice. 

When I am forced to ignore their advice, I struggle, fight and do battle with problems that either should not be solved or certainly not be solved in the manner in which I am forced to solve them. 

Should the study of and contribution to the body of knowledge of data management be called data-graphy or data-logy? 


The term Datagraphy sums up the study of the data management body of knowledge succintly. 

I refer back to the dictionary definition of the suffix "-graphy": "a process or form of drawing, writing, representing, recording, describing, etc., or an art or science concerned with such a process"

Data is recorded, described, written down,written about, represented (in many ways) and used as a source for many drawings and graphical representations. 

What do you think? I will certainly be using Datagraphy.
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1 comment:

  1. Datagraphy is the better choice. Datalogy had already been proposed by Peter Naur for ``the science of the nature and use of data'' in 1966. Unfortunately computer science did not catch on, so many people talk about "information" or "knowledge" when they refer to nothing more but plain old data.