Exclusive Research from2016

Data &Analytics
SurveyBig Data and Its Use
Cases Keep Growing
Companies still consider data-driven initiatives potentiallytransformative, and younger employees say the transformation is coming soon.
As companies continue to collect an ever-expanding amount of data, they're actively seeking more
ways to derive additional value from it. While enterprises with more than 1,000 employees are farther
down the road than smaller organizations (SMBs) in
implementing these data-driven projects, companiesof all sizes are investigating new analytic tools totackle an array of business goals. What's more, in what
may indicate a generational shift in IT expectations,younger participants in an IDG survey of 724 IT decision-makers who are involved in big data initiatives
are dramatically more likely than their elders to feelbig data will fundamentally alter the way business isdone in the very near future.
Based on total respondents, more than half (53%) of
their companies are currently implementing or planningto implement data-driven projects within the next 12months — that is, projects specifically undertaken withthe goal of generating greater value from existing data.
Out of the projects that are underway or in the planningstages, 26% are already implemented, 14% are in theprocess of implementation or pilot testing and 13% areplanning implementation in the next 12 months. Another 8% are considering a data-driven project, and 8% say
they're likely to pursue one, although they're currently

Data & Analytics Survey, IDG, 2016struggling to find the right strategy or solutions.
Among respondents who have no plans for a data-driven project, more than a third (38%) say they haveno need to derive additional information or analytics
from existing data. However, 22% cite budgetary constraints, and 21% say they don't have enough data.
Given their greater resources, enterprises are more
likely than SMBs to have already launched or to be in theprocess of launching a data-driven project. SMBs are
more likely to be struggling to identify the right strategy or solution for a data-driven project, or to have noplans to pursue one. The reasons why are contradictory,
though. On the one hand, many SMBs report that they
don't need any further information from the data they
have. On the other, they're five times more likely thanenterprises to say they lack sufficient data.

The Emerging Generation Gap
Overall, those who are implementing data-driven

projects, or plan to do so, feel big data offers enormous
opportunities. Across all company sizes, 78% agree orstrongly agree that the collection and analysis of big data
has the potential to fundamentally change the way theircompany does business in the next one to three years, andPage 2

71% agree or strongly agree that big data will create newrevenue opportunities and/or lines of business for theircompany in the same timeframe. While only 58% agree
or strongly agree that their company is positioned wellto capitalize on big data's potential, two-thirds (65%) are
optimistic that their organization's big data ecosystem
will begin to take, or change, form in the next year.
Interestingly, though, these responses differ notably
depending on the age of the respondent. Those aged 1834 are vastly more likely than other age groups to strongly agree on both the transformative potential of big data
and their companies' readiness to take advantage of it.
Meanwhile, those over 55 years of age are significantly
more likely than other age groups to disagree that big
data will open up new revenue opportunities and/orlines of business in the near future. They're also far moreunsure about whether and how their big data ecosystem
will change in the next 12 months.

These age-linked differences
may be attributable toyounger employees being
more comfortable with thelatest technologies and moreinured to the inevitability oftechnology-driven disruption.
On the other hand, older
respondents have seen many
supposedly transformational
technologies come and gothroughout their careers. It's
possible that they're simply
less willing to predict that any
particular trend — even one as
far-reaching and multifaceted
as big data analysis — will be asource of fundamental change.

Data & Analytics Survey, IDG, 2016

Data Goals and Pain Points
Respondents' top three business objectives ininvesting in data-driven initiatives are improving customer relationships (55%), making the business moredata-focused (53%), and changing the way operations
are organized (41%). Unsurprisingly, given budget realities, SMBs are significantly more likely than enterprises to cite reorganizing operations and optimizing thesupply chain.
The top three challenges organizations hope to solve
through data-driven initiatives are finding correlations
across multiple disparate data sources (60%), predicting
customer behavior (47%), and predicting product orservice sales (42%). While identifying computer security
risks, analyzing high-scale machine data and predicting
fraud and financial risk were lower on the list of challenges overall, they were higher priorities for enterprises. And interestingly, respondents aged 18-34 weresignificantly more likely than others to mention the needto analyze social network comments for consumer sentiment — possibly reflecting how tightly participation insocial media is woven into the lives of this age group.
Yet implementing these initiatives can itself be achallenge. In fact, 90% of respondents say they've experienced pain in one of these areas: data access and analysis
ranks as the number one headache instigator (38%),
data transformation (17%), data creation and collection(13%), data migration (13%), and data storage (10%).

Where Data Comes From
Respondents say that on average, 54% of the data
their organization views and analyzes is generated internally, while 25% is generated externally, and 21% comesfrom a combination of the two.
The types of data collected vary by company size.
Enterprises are more likely to collect transactionaldata, machine-generated/sensor data, government andpublic domain data, and data from security monitoring.
Smaller organizations, by comparison, tend to collectemail, data from third-party databases, social media, andstatistics from news media. Regardless of company size,
though, the top three sources of data are sales and financial transactions (56%), leads and sales contacts fromPage 3

customer databases (51%), and email and productivity
applications (tied at 39%).
Due to its disorganized model and lack of a pre-defined database, managing unstructured data (emails,word documents, presentations, etc.) creates a challenge
for organizations. Only 17% of organizations say that
unstructured data is a primary focus of their data-driven
initiatives, while nearly half (45%) call it one of theirbiggest challenges, and 31% say it is a problem that they
have under control. On the other hand, another 17% say
it's not on their short list of priorities, and 12% say it's
not a problem.

Data and Dollars, by Size
Given the volume and variety of data organizations

deal with, and the expense of managing it, it's no wonder
respondents have such high hopes — and a hard timeachieving them. Almost a quarter of respondents (19%)
are managing less than a terabyte of data, while only
7% are managing more than a petabyte. Although theaverage company manages 162.9TB of data, the average
enterprise has 347.56TB of data, seven times as muchdata as the average SMB with 47.81TB.
Similarly, organizations of all sizes expect theamount of data to increase considerably in a relatively
short timeframe. The average company expects its data
volumes to grow to 247.1TB, an increase of nearly 52%,in the next 12 to 18 months. The average enterprise's
data will grow slower than that, increasing by only 33%
to 461.25TB. The average SMB organization expects tosee its data volumes more than double, growing 138%
to 113.82TB. However, don’t put too much focus on thisnumber; in 2015 small organizations said their data
volume would grow to 110.6TB by 2016.
Under the circumstances, it’s no wonder the average
respondent plans to spend $7.93 million on data-driven
initiatives in the next 12 months. Enterprises plan toinvest a significant amount more than SMBs, with anaverage expected spending of $13.9 million versus $4.3
million for SMBs. Despite this jump in spending, almost
as many respondents expect their IT budget allocation
for data-driven initiatives to remain the same in the next
12 to 18 months (35%) as expect it to rise (44%). This

Data & Analytics Survey, IDG, 2016

holds true across all company sizes.
Ninety percent of respondents expect to have to invest
in the data center to keep up with data-driven initiatives
in the next 12 to 18 months, primarily in storage capacity,
data security, and cloud management. Similarly, 89%
expect to invest in solutions to derive further businessvalue from data, with data analytics, data/application
integration, and data visualization at the top of the list.
No one big data technology takes the lead, though: 46%
plan to invest in some part of the Hadoop ecosystem in
the next year, 41% plan to invest in a NoSQL solution,and 39% cite some other technology. Hadoop is the clear
winner among enterprise organizations – 52% have plansto adopt some form of Hadoop ecosystem versus 42%
SMB, while 44% of SMBs have plans to invest in NoSQL
compared to 38% of enterprises.

Big Data, Big Security Concerns
While raw data is valuable, the results of analysis areeven more so — and enterprise organizations are more
likely to appreciate the results of their analysis comparedto SMBs. Nonetheless, only 39% of respondents overall
say their company is securing the output of big data withalternate or additional security measures, while 44% say
the measures they're taking to secure existing data are
adequate to protect the results of analysis, too. The mostpopular approaches to securing big data output are identity and access controls (59%) and data encryption (52%),
with data segregation (42%) a distant third.
Interestingly, conformance with industry standards
for security is low on the overall list of criteria respondents cite as important when evaluating an offering froma data and analytics vendor — far behind ease of integration, ease of use, support and services, and scalability.
However, enterprise organizations have this vendor
criteria tied as the third most important factor. It's possible that some companies, especially SMBs, are trusting
their vendors to handle security concerns. The averagecompany's big data storage and analytics tools are just
18% cloud-based, but SMBs are nearly twice as likely asenterprises to have 50% or more of their big data storage
and analytics in the cloud.
It's also possible that companies don't feel the data
they're collecting requires further protection, since 68%

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either do not collect sensitive data (e.g. financial information, personally identifying information, or medicalrecords) or restrict how much they collect. Among thatgroup, half cite the need to meet compliance mandates,
while 38% have concerns about their ability to store thisdata securely, and 37% say they don't need to collectsensitive data. Enterprises are far more likely to limit
data collection for compliance purposes, while SMBs are
more than twice as likely as larger companies to say theydon't need sensitive data in the first place.
Whether it be security concerns, overabundance, orinability to effectively analyze data, there are multiple
reasons why organizations may seem stagnant whenit comes to data and analytics progress. Nonetheless,big data and analytics terminology has become mainstream and is no longer in the “hype” stage. In orderto stay ahead in this time of digital disruption and implement effective tech projects, organizations are andwill continue to invest in their raw numbers and create
actionable data.

Methodology
IDG conducted its 2016 Data & Analytics survey togain a better understanding of organizations' big data
initiatives, investments and strategies. A total of 1,060
respondents participated in the survey and results in thisreport are based off of 724 respondents who reported
their organizations are currently implementing, planningor considering big data projects. Audience members of
six IDG brands (CIO, Computerworld, CSO, InfoWorld,ITworld and Network World) were asked to take thesurvey via pop-up and email invitations.
A broad range of industries are represented including
high tech (18%), education (11%), financial services (11%),
manufacturing (9%), government (9%), professional ser-

Data & Analytics Survey, IDG, 2016vices (7%), healthcare (7%), and telecommunications andutilities (6%. Two out of five respondents (41 %) work inorganizations with 1,000 or more employees while 58 percent work in companies with fewer than 1,000 employees(1% indicated they were not sure).
Over a third (47%) of respondents indicated they are a
top IT executive at their company or business unit/location. Fifty-two percent of respondents hold executive IT
management titles, 17 percent hold mid-level IT management titles, 14 percent hold IT professional titles, 12
percent hold business management titles and 5 percent
hold other titles.

The margin of error for a sample sizeof 724 is +/- 3.6 percentage points.
The margin of error for a sample sizeof 1,060 is +/- 3.0 percentage points.
For the purposes of this report,“enterprise” refers to organizations
with $1 billion or more in annual
revenues, “mid-market” refers
to organizations with $100 - 999
million in annual revenues and“small” refers to organizations withless than $100 million in annual
revenues. For questions requiring
respondents to select a single
answer, percentages may not sum to100 percent due to rounding.

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Data & Analytics Survey, IDG, 2016

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Examining the Marketplace
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Buying Process

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Data & Analytics Survey, IDG, 2016

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