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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Data is killing us!

Are you drowning in Data?

You have a number of applications collecting various pieces of data in order to run your business. What do you have to do in order for an analyst to make an informed decision?

For the majority of your business operations, dashboards should show current activity. Thresholds can be established for when a particular event takes place and alerts sent automatically. Simulations can be run based on past performance to gauge or even predict the performance of what-if scenarios.

All of these things can be done, the question is: Are they being done?

EMC Symmetrix DMX1000 Disk ArrayImage via Wikipedia

Are there so many copies of your application databases, that the cost of servers, disk arrays and storage going through the roof?

Are multiple people required to keep track of which backups and restores are done on a nightly basis driving personnel costs up?

Are business analysts spending more time collecting data than understanding, interpreting and making recommendations, reducing efficiency?

There is a better way.

A person who studies the practices of data management and the applicability of the various data management tools, procedures or methodologies to the needs of the business can make a difference in the use of an organizations data.

This difference can be measured in many ways. It could be an increase in revenue because a relationship was found in the data that could not have been seen before a new business intelligence system was deployed. It could be cost savings of physical equipment.

More often it is the saving of personnel time associated with gathering data just to answer questions.

Some proponents of vendor solutions will suggest that they have all of the answers to your data needs. Perhaps some vendors do have solutions. However, bringing in a vendor solution will not relieve an organization of the responsibility of data management.

The best way to work with vendors is to get them to fully understand all of the pain points associated with your data. No single vendor can solve all problems. Smart people with a vested interest in making your company successful will help you management your data.

Proliferation of data makes an organization stronger. If data is killing you, then you need someone to tame the beast and make data work for you.

Make your data work for you, rather than you work for your data.

Who are the people that will make your data work for you? A database administrator is a good start, many I have spoken to have plenty of ideas for how to make things better.

A data architect is the best start. Data Architects are the people that have studied data management best practices. A great Data Architect can quickly come to an understanding of your pain points and make recommendations that can be done soon to make sure that data works for you.

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