Data Management
An overview
of
Data Management in the form of some clusters of component tasks may
serve to illustrate the concepts. Most people have
a
difficult time holding on to an abstraction long enough to affect it.
For example, "circle" is an abstraction whose defintion
a simple shape of Euclidean geometry consisting of those points in a plane which are at a constant distance, called the radius, from a fixed point, called the center
is meaningful only to those relatively few people who understand the concept of "plane" and "shape" and aren't intimidated by "Euclidian geometry." Everyone else needs to see a concrete example in the form of a simple picture.
"Data" is even more difficult because we can't draw a meaningful picture. The best comparison may be "money."
Everyone is familiar with the concept of money and can produce many examples of apparently dissimilar things that are all money. At its root, money is an idea that manifests in many different forms, all having a purpose involving the transfer or documentation of wealth.
While the underlying purpose of all data is to capture and convey information, data goes beyond money as an idea because the purpose--and value--of data (your bank statement for example) may change depending upon several factors including:
- the intent of the originator
- the intent of the holder
- who is holding the statement
- how old the statement is
- how well it agrees with your own version (your check register, for example)
As with the money abstraction, it is only by means of
- carefuly constructed definitions
- well documented relationships
- commonly understood processes
that data can achieve it's full value.
Data Management is the activity of creating those definitions, relationships and processes as well as a governance activity to ensure that definitions, relationships and processes are used consistently and appropriately. It includes data and process architecture, data administration, database administration, master (reference) data management, meta data management data quality, quality assurance and control and the governance structure to connect them all.
The best information for the best decision.