Based on the survey more than 90 respondents agree

Based on the survey, more than 90% respondents agree that with Big Data they
can take better-informed business decisions by analyzing more data than they are
currently processing. However, only 57% respondents agree that existing Big Data
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93%
6% 1%
We can make more informed
decisions by analyzing more data
than we do now
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Respondents were asked if they agree or disagree with the above statements with
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Agree < on’t know < isagree
57%
33%
10%
We understand business bene Õ ts of
: ig < ata tech and solutions
Figure 9. Big Data technology awareness
Respondents were asked to rate their current awareness level of existing
Big Data technology components
19%
20%
16%
12%
15%
15%
18%
15%
65%
63%
56%
65%
65%
63%
51%
57%
16%
17%
27%
23%
21%
23%
31%
27%
0% 20% 40% 60% 80% 100%
Non relational databases (e.g: NoSQL)
In-memory databases
Scale-out architechtures
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Distributed indexing and search
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Distributed data analytics engines
Rule-based stream processing engines
Multiple parallel processing systems
=pl]fkan] cfgod]\_] Limited knowledge Totally unfamiliar
Big Data tech solutions
not well understood
Low awareness of
components related
to technology stack
limiting Big Data
adoption

Big Data and Enterprise Mobility 20
Recently Big Data has gained prominence in the Indian landscape; however, most
organizations in India have limited knowledge of various components that form part
of a Big Data technology stack. The current awareness levels are low, since nearly
75% respondents have limited knowledge of the tech components and less than 20%
respondents believe they have extensive knowledge and can further drive adoption
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Sponsorship is important to drive Big
Data adoption
During initial stages of adoption, the CIO drives the technology investments related to
Big Data solutions. However, as organizations move up the adoption curve, Big Data
related initiatives will require sponsorship from business leaders to drive business
insights. A single sponsorship model with function heads such as CFO, CMO and others
will remain critical for Big Data success.
CFOs can use analytics to assess, benchmark and identify gaps across various forms
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CMOs can leverage Big Data analytics to determine the effectiveness (the impact on
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including media, trade promotions and consumer promotions. In addition, insights
related to environmental factors such as competitor activity, price changes and
category factors could be analyzed using advanced techniques to drive marketing and
promotion strategies.