The document discusses challenges faced by IT teams in big data projects. It finds that 55% of big data projects are not completed due to inaccurate scoping, technical roadblocks, and siloed data. Only 6% of enterprises list big data as a top 10 IT priority. When it comes to analytics projects, the top reasons for failure are lack of expertise to connect insights and lack of business context. Real-time and batch analytics are both important. The most significant challenges for big data projects are finding the right tools and allocating time. IT teams believe data scientists, application developers, and business users can most impact revenue through increased access to enterprise data.

1. CIOS & BIG DATA
What Your IT Team Wants You to Know
of Big Data projects
55% are not completed
WHY?
! [ ] [ ]
58% 41% 39%
inaccurate scope technical roadblocks SILOED DATA AND
NON-COOPERATION
O
of enterprises do not have Big Data
6%
n
l
y
in their Top 10 IT Priorities list
Outside of Big Data, top priorities are
mobile, dashboarding, and website
100
75
48%
47%
50
45%
25
0
all taking place at the app layer above the infrastructure stack
When it comes to analytics projects
the top 2 reasons cited for failure are
lack of expertise
to connect the dots & lack of business
context around data
batch analytics
- and -
Real-time analytics
are almost equally important
When it comes to phases of big data
projects, these pose the most difficulty
43% Processing the data
42% ongoing mgmt of the data
41% analyzing the data
When it comes to big data projects,
the most significant challenge faced is
76% 75%
80% finding the
right tools
time
73% 72%
finding talent understanding education
the platforms
Top requirements of
big data
solutions
Ease of
#1 management
Ability
#2 to scale
Flexible
#3 architecture
Speed to
#4 Deployment
IT teams believe that while it is important for Executive Management
to have increased access to enterprise data, those who have the
greatest ability to impact bottom line revenue as a result of
increased access to enterprise data are:
Data Scientists and Analytics Staff
followed by
Application
Developers & Business
Users
January 24, 2013
*Infochimps and SSWUG.ORG queried more than 300 IT department employees for this report in fall
of 2012, 58% of whom identify themselves as currently being involved in big data initiatives.
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