stack is not easy, and most IT organizations don’t yet allow for easy integration.
This integration quickly becomes critical
when one moves beyond experimentation into solving real-world business
problems that require multi-dimensional
data, some of which might be in legacy
enterprise data warehouse (EDW) environments [4]. Second, while strong use
communities around open source technologies exist, the learning curve could
be longer given the often less than user-friendly nature of these technologies.
Learning on open source requires a certain level of existing expertise, and beginners may find a learning approach based
on open source harder.
Integrated Big Data Analytics
Platform
Most analytics for business use cases
rely on bringing together diverse data sets
to analyze. With big data, these data sets
are no longer limited to just structured
data; they increasingly leverage unstructured data as well. This calls for a big data
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DOMAINS OF ANALYTICS PRACTICE
Domain
Description
Weight*
Business Problem (Question) Framing 15%
I
Analytics Problem Framing
II
17%
III Data
22%
Methodology (Approach) Selection
IV
15%
Model Building
V
16%
VI Deployment
9%
VII Life Cycle Management
6%
*Percentage of questions in exam
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a na l y t i c s
s e p t e m b e r / o c t o b e r 2 014
100%
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