Specifications

126 CHAPTER 7 Master Data Services
This scenario presents additional problems for operational master data in an organiza-
tion because there is no coordination across multiple systems. Business users cannot be
sure which of the many available systems has the correct information. Moreover, even when
a user identies a data quality problem, the process for properly updating the data is not
always straightforward or timely, nor does xing the data in one application necessarily ripple
through the other applications to keep all applications synchronized.
Compounding the problems further is data that has no ofcial home in the organization’s
data management infrastructure. Older data might be archived and no longer available in
operational systems. Other data might reside only in e-mail or in a Microsoft Access database
on a computer sitting under someone’s desk.
Some organizations try their best not to add another system dedicated to master data
management to minimize the number of systems they must maintain. However, ultimately
they nd that neither existing applications nor ETL processes can be sufciently extended to
accommodate their requirements. Proper master data management requires a wide range of
functionality that is difcult, if not impossible, to replicate through minor adaptations to an
organization’s technical infrastructure.
Last, the challenges associated with analytic master data stem from the need to man-
age dimensions more effectively. For example, analysts might require certain attributes in a
business intelligence (BI) solution, but these attributes might have no source in the line-of-
business applications on which the BI solution is built. In such a case, the ETL developer can
easily create a set of static attributes to load into the BI solution, but what happens when
the analyst wants to add more attributes? Moreover, how gracefully can that solution handle
changes to hierarchical structures?
Key Features of Master Data Services
The goal of MDS is to address the challenges of both operational and analytical master data
management by providing a master data hub to centrally organize, maintain, and manage
your master data. This master data hub supports these capabilities with a scalable and exten-
sible infrastructure built on SQL Server and the Windows Communication Foundation (WCF)
APIs. By centralizing the master data in an external system, you can more easily align all busi-
ness applications to this single authoritative source. You can adapt your business processes to
use the master data hub as a System of Entry that can then update downstream systems. An-
other option is to use it as a System of Record to integrate data from multiple source systems
into a consolidated view, which you can then manage more efciently from a central location.
Either way, this centralization of master data helps you improve and maintain data quality.
Because the master data hub is not specic to any domain, you can organize your master
data as you see t, rather than force your data to conform to a predened format. You can
easily add new subject areas as necessary or make changes to your existing master data to
meet unique requirements as they arise. The master data hub is completely metadata driven,
so you have the exibility you need to organize your master data.