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Unformatted text preview: bal companies are taking drastic measures to deal
with the downturn and remain profitable. However,
these measures are often predicated on the assumption
that decision-makers have access to a clean and
comprehensive set of corporate data with a sufficiently
granular level of detail.
The devil is often in the detail. For example, many
decisions taken to maximize revenues or profitability
are based solely on financial information that does
not necessarily reside in a single financial system.
Companies should closely scrutinize decisions and
pull together all the information about the products,
customers, services, and geographies that are
contributing most to the overall profit. However, many
organizations struggle to bring together this information
because it is strewn across separately managed systems
with differing levels of control and quality. More data usually means silos and poorer quality
Electronic data proliferation is economically neutral in that
it grows exponentially in good times or bad. Databases
have increased in number, size, and the richness of
detail they contain. Attempts to tame this data growth in
business applications such as ERP, CRM, supply chain
management, and other enterprise business systems work
on the assumption that data will remain in those siloed
environments, but the reality is that companies often install
multiple ERP and CRM packages for different units and
Due to incompatible system design, moving data between
environments is never a simple copy-and-paste task
because each application has its own nuances and
peculiarities regarding how disparate data is formatted,
labeled, and stored. Common data quality issues, such
as inconsistent data entry, duplication of records across
database systems, incomplete and missing data elements, 6 S TRAIGHTTALK I T and confounded product hierarchies, also present obstacles
to data consistency. No automatic wash cycle for data quality
Treating data quality as something that can be solved by a
piece of IT has also exacerbated the problem. Corporate
data cannot simply be coll...
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This document was uploaded on 12/31/2013.
- Fall '13