Databases Reference
In-Depth Information
Data quality measures provide means to fix data related issues already
existing in the organization whereas MDM, if implemented properly,
prevents data-quality-related issues from happening in the organization.
Metadata management deals with the softer side of the data-related issues, but
it is one of the key enablers within the purview of information lifecycle management.
The simplest
definition of metadata is “data about data
.” In other words, metadata can
be thought of as a label that provides a definition, description, and context for data.
Common examples include relational table definitions and flat file layouts. More detailed
examples of metadata include conceptual and logical data models.
A famous quote, sometimes referred to as “Segal's Law,” states that: “A man with
one watch knows what time it is. A man with two watches is never sure.” When it comes
to the metrics used to make (or explain) critical business decisions, it is not surprising
to witness the “we have too many watches” phenomenon as the primary cause of the
confusion surrounding the (often conflicting) answers to common business questions,
such as:
•
How many customers do we have?
•
How many products did we sell?
•
How much revenue did we generate?
Therefore, another example of metadata is providing clear definitions of what the
terms “customers,” “products,” and “revenue” actually mean.
Metadata is one of the most overlooked aspects of data management, and yet it is the
most difficult initiative to implement. Metadata can potentially encompass many levels;
from a single data element on the database to a more complex entity, such as customer,
for example, which will be a composite of other elements and/or entities.
■
The topic of information lifecycle management and especially data quality, master
data management and metadata management are itself separate chapters on their own.
Here we have given brief overviews about these important concepts as they relate to data
and its management.
Note
8.
Regulations and Compliance:
Irrespective of which industry
your company belongs to, regulatory risk and compliance is of
utmost concern. In some industries like financial services and
health care, meeting regulatory requirements is of the highest
order; whereas other industries may not be exposed to such
strict compliance rules. EIM helps you address the regulatory
risk that goes with data.
