BI Data Management
Data management includes all the disciplines related to managing
data as a valuable resource. It is commonly referred to as Data
Resource Management, which is defined as "the development and
execution of architectures, policies, practices and procedures that
properly manage the full data lifecycle needs of an enterprise."
Why Data Management Is Iimportant
A Teradata survey in 2005 revealed that "over 80 percent
of executives surveyed in Europe, Australia and New Zealand said
that data has increased over the past five years and about 70 percent
expect the increases to continue for the next five years"....that
has driven data solutions to the forefront of business capability.
"Significantly, 71 percent say they are using or moving toward
enterprise data warehousing
.....And close to 90 percent of all respondents say that enterprise
data warehousing improves company profitability, productivity and
long-term growth, with over 80 percent citing customer service and
What is Data Management?
Data Management includes a number of data related processes and
Data Management In Business Intelligence
Data Management should be isolated from application development
in the BI Program.
A lot of BI programs are constrained by lack of data delivery knowledge.
BI maturity is aligned with DM maturity, meaning data needs to
evolve in step with the applications being delivered. If this is
done managed, analytic capability will be severely constrained and
users will become frustrated, risking adoption of the entire BI
Measuring Data Management Capabiltiy
BI Project Scorecards are a good way of managing the alignment
of data development and application development.
Data maturity is not just in data
integration but also in the usage of data as a business asset:
- Reuse - the sharing and reuse of data across the organisation
- Robust data modelling capability
- Ancillary meta data backed into each BI projects, in increments
Usage of data is a KPI of BI.
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