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Nearly all asset management
firms are involved in some form of data management project. The pressures to manage data are intense. They are driven
by many factors, including the complexity of business,
globalization, mergers and growth in new business areas, as
well as more tactical issues, such as multiple independent
data feeds, disparate systems and data formats, and of
course the regulatory environment. The sheer volume of data
is overwhelming; for example, a large, global firm typically
tracks daily pricing and other details on 250,000 securities
and maintains scrubbed upstream daily and historical records
on 50,000 securities. Add to the mix corporate actions,
enrichment of data by investment professionals and trading
data.
With this
demanding market environment, data must be accurate,
complete, timely, integrated and above all, trusted. Every
new securities market entered, operations process
established, initiative launched and application implemented
has an underlying data component. As firms address these
data issues, they come to understand that data management is
not only an IT issue – it is a firm-wide challenge that
involves:
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Identifying data requirements
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Evaluating and testing multiple sources of data
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Cleansing, reconciling and completing sourced data
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Storing and safeguarding data while preserving its accessibility
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Distributing the data
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Purging
or archiving the data as required
Data
quality does not just happen – it occurs because careful
steps are taken to establish objectives, responsibilities
and supporting processes and metrics that institutionalize
comprehensive data quality practices.
For leading
firms this takes the form of a commitment to establishing a
data governance function - a program whereby data is
considered an asset of the firm, equal in importance to
financial and material assets. It ensures that data quality
is an ongoing strategic initiative. The adoption of data
governance practices provides the framework, structure and
organization to manage data effectively.
Solid,
world-class data governance programs are intentional, not
accidental. They are planned and implemented just like any
other strategic initiative:
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They
have a clear definition both strategic and tactical
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The
internal and external factors impacting data quality are
clearly articulated and understood
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Roles
and the responsibilities are clearly defined
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Standards are identified along with metrics to quantify
compliance
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An
organizational structure to support the program is
implemented
The
adoption of a data governance program provides clear
direction and structure for the data management function. It should be organized to be the full-time equivalent of a
project steering committee with CEO sponsorship. Its
presence promotes the acknowledgement of the importance of
data within your organization, giving it the same attention
as your firm’s most valued assets. In addition, data
governance is a conduit to maintaining consensus among the
business, operations and IT areas. The overall objective of
a data governance program is to have a firm-wide perspective
and span of control, with the goal of ensuring that the
required data is available, complete, timely and accurate.
Data is
strategic – managing it is not. Bad data and poor data
management are costly and introduce risks that are not
tolerated in this world of tighter controls and
accountability. A comprehensive data governance program
will provide a secure foundation, enabling quality data to
support business endeavors and future growth, thus escaping
the risky, fragmented, uncoordinated and burdensome drain
that data management often is today.
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