Database Reference
In-Depth Information
Challenges and barriers of effective BI
The need to deliver accurate information quickly is the fundamental challenge for
Business Intelligence. The production of high quality information in a useful format
takes time—data must be acquired, cleansed, modeled, and stored over continuous
update and enhancement cycles. If any of these aspects of properly managing data
are given less than appropriate attention, the quality of the information suffers—you
take a short cut for speed of delivery and risk a reduction in the quality of the final
product.
Even the highest quality information is of little value if it comes too late to be helpful.
So the pressure is on meeting the business requests for information now, not in the
several days or weeks it might take to define requirements, update the data model,
develop ETL processes, test, validate, and finally make the information available in
the data warehouse. Businesses often cannot wait and so they develop alternatives
for acquiring and "managing" their own data. These alternatives, though they may an-
swer the need for speed, inevitably result in both redundant data and inconsistent in-
formation.
Over time, technology and business groups have developed strategies and tech-
niques aimed at coming closer to aligning managed data and the much faster busi-
ness cycles. Improvements in traditional data storage engines, including the devel-
opment of multidimensional models and ETL tools have helped. Iterative and agile
development methodologies have given BI more of a continuous improvement than
waterfall behavior and have made the environment more nimble. Still, there remained
a gap where IT could not respond quickly enough to business demands, and busi-
nesses did not have the skill and discipline to sufficiently manage high quality data.
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