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Supporting MDM
Along with setting up a
Total Data Quality solution, you will need
to deal with the other challenge of MDM – mainly, the deduplication
of data from disparate sources with the integration provided by SSIS.
An MDM application that combines data from multiple data sources
might hit a roadblock
merging the data, if there isn’t a ‘unique
identifier’ that is shared across the enterprise. This typically
occurs when each data source system (i.e. an organization’s sales
division, customer service department or call center) identifies a
business entity differently.
There are three general categories or ways to organize your data so
that it can ultimately be merged for MDM solutions – they are unique
identifiers, attributes and transactions.
Unique identifiers – These identifiers define a business entity’s
master system of record. As you bring together data from various
data sources, an organization must have a consistent mechanism to
uniquely identify, match and link customer information across
different business functions. While data connectivity provides the
mechanism to access master data from various source systems, it is
the Total Data Quality process that ensures integration with a high
level of data quality and consistency. Once an organization’s data
is cleansed, its unique identifiers can be shared among multiple
sources. In essence, a business can develop a ‘single customer view’
– it can consolidate its data into a single customer view to provide
data to its existing sources. This ensures accurate, consistent data
across the enterprise.
Attributes – Once a unique identifier is determined for an entity,
you can organize your data by adding attributes that provide
meaningful business context, categorize the business entity into one
or more groups, and provide more detail on the entity’s relationship
to other business entities. These attributes may be directly
obtained from source systems.
While managing unique identifiers can help you cleanse duplicate
records, you will likely need to cleanse your data attributes. In
many situations, you will still need to perform data cleansing to
manage conflicting attributes across different data sources.
Transactions – Creating a master business entity typically involves
consolidating data from multiple source systems. Once you have
identified a mechanism to bridge and cleanse the data, you can begin
to categorize the entity based on the types of transactions or
activities that the entity is involved in. When you work with
transaction data, you will often need to collect and merge your data
before building it into your MDM solution.
Next Step:
Building Support for Compliance and Data Governance
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