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Lonispace has significant years of
experience in the practice of Master
Data Management (MDM) specifically
related to integrating enterprise
data in an orderly and structured
manner as it is externalised via
various interface types and or data
models and presented to the
enterprise for use in other
applications or environments (i.e
part of an SOA architecture or part
of a compliance and governance
reporting repository).
Our aim is to offer a recommended
best practice approach for our
customers when they are wrestling
with a resolution to their common
data integration challenges such as
integrating data and applications
and the need to identify and cleanse
similar data objects across various
systems while enabling the
possibility of an agreed common data
model structure across the
enterprise.
To provide the best practice
approach Lonispace has invested
considerable resource in the
investigation, implementation and
review of various data integration
projects. At the end of this
extensive effort that was conducted
over a period of years we have
adopted the view that Master Data
Management (MDM) is the overriding
approach to data stewardship that
has as its core focus the
management, validation, cleansing,
audit and reconciliation of all data
elements throughout the integrated
enterprise.
To achieve a best practice
approach to MDM Lonispace has drawn
upon its vast experience in
information and data integration
projects to be able to define a
consistent best practice approach
and to describe all the key elements
that support this proposed MDM
approach. The key components that
comprise our best practice MDM
approach are; Information Modelling
Best Practice, Information Model
Implementation Framework, Services
Oriented Architecture Best Practice
and Data Modelling best practice.
Data Modelling typically brings
to mind a database and how to best
structure, fine tune and deploy
content for an application, a data
warehouse or an operational data
store. There has been numerous
books, documents and white papers
written on how best to construct,
fine tune and deploy data bases of
these types and therefore it is not
our intention to attempt to add to
this already well documented
disclipine in managing your data
silos. Rather our focus is on the
notion of integrating enterprise
data in a more orderly and
structured manner as it is
externalised via an interface of
some type and presented to the
enterprise for use in other
applications or environments (i.e
part of an SOA architecture or part
of a compliance and governance
reporting repository), we have
defined this overall approach as
Master Data Management (MDM).
One of the most important
outcomes of Data Modelling is a
concrete understanding of the
implemented data within the
organisation. Within the context of
MDM the Data Model is a realisation
of the Information Model (please see
Information Modelling Best Practice
for a further explanation) and the
rules which have been embraced
within its development. When
combined with the enterprise
Information Model your organisation
can resolve a solution that ensures
the movement of business content
throughout the organisation's
technology enterprise in the most
efficient and cost effective manner
possible.
In summary, Lonispace offer an
MDM approach that is based on the
premise that data and information
integration are the key underlying
architectural principles.
For clarification purposes
Lonispace submit that the Data Model
is created to define the meaning of
the data within the Enterprise, its
values, and how the data
(operational or static content) is
related to it's structures. The
structure of the data will include
logical business entities and their
interdependencies as derived from
the Information Model. The process
of analysing the data to create the
Data Model is known as Data
Modelling.
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