Master Data Management
Master Data Management (MDM) represents
a set of tools and processes used by an enterprise to consistently manage their
non-transactional data. MDM is usually applied to entities like Customer,
Client, Product, Account and internal reference data. MDM also enables easy
maintenance of data lineage and history for audit purposes.
Issues
In the enterprise there are several
systems managing the same data; the role of MDM is to centralize the data
management to only one master copy of the data item which is then synchronized
to all applications using the data. Using this approach, when referring to (for
example) a customer within the enterprise, all systems are referring to the
same customer.
There are basically two reasons why
there are duplicated data which are inconsistent:
·
The production systems within an
enterprise, when implemented, have not been designed to be a part of larger set
of production systems with which they should cooperate. Therefore, each system
manages data on its own.
·
The branches or departments of
the company exist on their own without close cooperation with other
departments. For example, the mortgage department deals with customers and
manages the mortgage contracts. While the marketing department plans a
promotion on mortgages. If the two departments do not cooperate (share the
data), the marketing department may offer a mortgage to a customer who already
has a mortgage. This is both a waste of money on the promotion as well as
annoying to the customer.
·
Company acquisitions or mergers
are another example when an enterprise gets several parallel systems managing
similar and sometimes overlapping data.
Solutions
To handle the issues mentioned above,
the common baseline for Master Data Management solutions comprises the
following processes:
·
Source identification - the
'system of record' needs to be identified first. If the same record is stored
in multiple systems, the system which holds the most relevant copy (most valid,
actual, or complete) of that record is referred to as a 'system of record'.
·
Data collection - the data needs
to be collected from various sources as some sources may attach a new piece of
information, while dropping pieces which they are not interested in.
·
Transformation - the
transformation step takes place both during the input, while data are converted
into a format for MDM processing, as well as on the output when distributing
the master records back to the particular systems and applications.
·
Data consolidation - the records
from various systems which represent the same physical entity are consolidated
into one record - a master record. The record is assigned a version number to
enable a mechanism to check which version of record is being used in particular
systems.
·
Data deduplication - often there
are separate records in the company's systems, which in fact identify the same
customer. For example, the bank may have a record identifying a customer while
the bank's insurance subsidiary or department maintains a separate database of
customers having a different record for the same customer. It is vital that
these two records are deduplicated and maintained as one master record.
·
Error detection - based on the
rules and metrics, the incomplete records or records containing inconsistent
data should be identified and sent to their respective owners before publishing
them to all the other applications. Providing erroneous data may compromise
credibility of the company's MDM.
·
Data correction - related to
error detection, this step notifies the owner of the data record that there is
a need to review the record manually.
·
Data distribution/synchronization
- the master records are distributed to the systems in the enterprise. The goal
is that all the systems are using the same version of the record as soon as
possible after the publication of the new record.
Master Data Management Issues&Solutions
Reviewed by ramesh
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Reviewed by ramesh
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05:57
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