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Unlocking Potential with Data AnalyticsBig Data Priorities 2013

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2 BIG DATA PRIORITIES 2013

Con

tent

s 3 Executive Summary

7 About This Report7 About Big Data Priorities

7 About ZDNet and CBS Interactive

7 About Dun & Bradstreet

8 Current and Future Use of Analytics/Big Data

8 Analytics in Day-to-Day Business

10 The Growing Potential of Analytics/Big Data

11 Analytics/Big Data Products Measurable Financial Returns

12 The Data Perspective12 Obstacles to Maximizing Benefits from Analytics

13 Businesses are Tackling a Range of Data Issues

15 Types and Sources of Data Used for Analytics

16 Data-as-a-Service Providers (DaaS)

18 Survey Methodology18 Approach and Sample

18 Scope and Terminology

19 Timelines

19 Respondents

19 Respondent Demographics

About this custom report: This custom report has been prepared by CBS Interactive on behalf of D&B. D&B has specified topic,

title and key themes of this report and may have contributed to and exercised editorial control over the content. This report may

only be quoted and reproduced by D&B in its entirety.



The recent growth in utilization of analytics and big data has been matched by a growth in coverage in the business and technology media. Much of that commentary has focused on the emerging technologies like Hadoop, MapReduce and advanced analytics tools first deployed at leading online businesses such as Google, Facebook and Linkedin. These technologies provide the distributed storage and computing power by which massive quantities of heterogeneous data sets can be stored, processed and analyzed. That is the “Big” in big data.

What of the “data” in big data? This paper, a companion report to

ZDNet’s Big Data Priorities 2013 research study, reports on the types

of data organizations use in their big data initiatives, the sources of the

data, and the priority data issues.

ZDNet’s research shows many organizations have already deployed

analytics and/or big data, or are considering adopting it. Just fewer

than one-half of businesses (47.1%) use analytics in everyday decision

making and business processes today. A further 18.1% will deploy

analytics capabilities in 2013, raising membership of the analytics club to

65.3% of organizations.

Organizations clearly see the growing potential of analytics/big data.

Currently, just under one-quarter of organizations (23.8%) say analytics/

big data has high potential to have a major influence on their business

performance, but that number grows to 37.1% when respondents look

a year ahead (2013), and doubles to 50.3% when they look ahead to

2014.

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Almost all businesses that currently use analytics/big data say they derive measurable financial

benefits from it, but the extent varies. Around one-fifth (19.3%) have achieved major financial

benefits, and 6.4% report achieving financial benefits to a great extent.

However, organizations say some obstacles prevent them maximizing the potential benefits from

analytics, including not having analytics in their organization’s DNA, or they lack sufficient analytics

skills and data skills.

In responding to some of these obstacles, organizations are attending to many data issues, from

business focused topics like creating confidence in the veracity of data to more technical ones like

automating the extraction/transform/load (ETL) process, or policy issues like agreeing ownership and

governance of data.

The priority data issues for around two-thirds of organizations are providing usable data to the

business, doing so cost-efficiently, and within appropriate data security controls. The next group

of priority topics broadly focus on sourcing and integrating data (e.g. identifying new data sources

that can improve analytics outcomes), and are priorities for more than one-half of organizations. The

remaining data priorities, mostly to do with data policy, have lesser focus but are still important for

just under one-half of respondents.

Analytics-using organizations are hungry for data they can transform into business value. While

they are almost twice as likely to use internally-sourced data as they are to use data from external

sources, utilization of the latter has grown rapidly and will continue to do so.

Website activity is an important data source for analytics-savvy businesses, and the emergence of

sensors as a major data source attests to the growth of the Machine-to-Machine (M2M) ecosystem.

Businesses also source and buy data from commercial third-party data suppliers, a practice that is

becoming known as Data-as-a–Service, or DaaS. The use of data from DaaS providers will double

by the end of 2014. Dun and Bradstreet is the go-to source for DaaS, followed by Experian and

InfoUSA, according to respondents.

For analytics/big data exponents, mastering the new technologies is only one of the challenges.

Data challenges abound, not least the lack of deep data skills in many organizations. Where these

skills are made available – either in-house or through hiring external expertise – businesses can really

focus on maximizing the benefits of big data investments.

As the research shows, many organizations are already deriving measurable financial benefits from

their analytics/big data initiatives. By focusing more on the “data” in big data they stand to benefit

even more.

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How should businesses react? Recommendations:

1. Don’t be left behind

Forty-seven percent of businesses are already using analytics in everyday decision-making and

processes, and another 18% will start in 2013. If your business is not doing so, you’re probably at

a competitive disadvantage. Devise a clear plan to assess how analytics and big data can help your

business compete, and then begin to consider the ways to incorporate analytics into your business.

2. Ask yourself: “What do I wish I knew?”

Organizations sometimes don’t know where to start with analytics/big data. Begin by asking

yourself what critical pieces of information you’d love to know about your business. What would you

love to know about your customers, about the potential customers you don’t have who currently buy

from competitors, and about the markets in which you operate? The answers to these questions will

provide a priority list from which you can begin your analytics/big data journey.

3. Think about where you can find and manage the information or data you lack

You probably already have much of the data you need – from operational systems in your business,

and in the behavioral data you collect from your website traffic and your social presence. But is it

properly organized, is it available to people who make business decisions, do you have appropriate

data governance with rules about data ownership, standardization and rules for sharing? Look

outside the organization for data that plugs the holes in the data you already have. Good sources

include public data supplied through open government initiatives, commercial data-as-a-service

providers, and even social media feeds. Consider data sharing arrangements with non-competing

organizations.

4. Develop, hire and retain employees with data skills

Data science is a specialized craft. It’s a combination of statistics, mathematics and technology

know-how aligned with business domain knowledge and the ability to ask the right penetrating

questions about the data an organization holds. These people work with business leaders to unlock

the value of data in a business, and can answer the questions you “wish you knew.” You need to

find and retain the best people.

5. Gut feel? Get Real! Inculcate an analytics culture across your organization

An analytics mindset is not only for the data specialist. Businesses must foster the use of data

across the organization, and move away from decision by intuition, or “gut feel.” This is a change

process like any other you’ve used to move your organization from one cultural paradigm to another.

The senior leadership team must lead by example, and should employ the deep data skills of data

science specialists to coach line managers and their staff on how best to use data to inform their

decision-making every day.

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6. Do it!

Select the most important “I wish I knew” topic and get started.

Make the business case for your priority data project, state the investment and targeted financial

return and challenge your business leaders and data specialists to deliver. You’ll learn from your

mistakes, find opportunities you weren’t aware of, and you’ll develop your institutional data

competencies.

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About Big Data Priorities

Part of ZDNet’s IT Priorities research series, Big Data Priorities 2013

(http://i.zdnet.com/whitepapers/ZDNet_Big_Data_Priorities_2013.pdf)

is a survey about the analytics/big data strategies, challenges and

implementation priorities of IT leaders.

This paper, Big Data Priorities – The Data Perspective is a special report

commissioned by Dun & Bradstreet, sponsors of the overall Big Data

Priorities project. As the name suggests, the paper reports on the types of

data organizations use in their big data initiatives, the sources of the data,

and the priority data issues.

Please refer to the methodology chapter at the end of this report for more

information about the report scope, respondent base and topics covered.

About ZDNet and CBS Interactive ZDNet (www.zdnet.com) is where technology means business. The site

attracts an enthusiastic and interactive audience of business technology

influencers, many of whom visit for the latest coverage and analysis of how

technology impacts business.

Business leaders and decision makers including CEOs, CIOs and IT

professionals at all levels value the site due to its extensive resources,

enabling them to make the most out of technology for their business

challenges.

To provide context for this report, this section briefly discusses the current

use of analytics/big data and respondents’ evaluation of the potential future

benefits. For more details on this and related topics please refer to the full

report, Big Data Priorities 2013.

About Dun & Bradstreet D&B (NYSE:DNB) is the world’s leading source of commercial information

and insight on businesses, enabling companies to Decide with Confidence

for more than 170 years. Today, D&B’s global commercial database contains

more than 205 million business records. Enhanced by D&B’s proprietary

DUNSRight™ Quality Process, the D&B database provides our customers

with unparalleled quality business information -- the foundation of our

global solutions that customers rely on to make critical business decisions.

D&B provides solutions that meet a diverse set of global customer needs.

D&B offers Data-as-a-Service solutions that deliver streaming D&B insight,

like financials, risk analysis, company profiles and more, directly into any

enterprise or custom application to help companies make smarter decisions

and grow their business.

Abo

ut th

is re

port

http://i.zdnet.com/whitepapers/ZDNet_Big_Data_Priorities_2013.pdf

http://i.zdnet.com/whitepapers/ZDNet_Big_Data_Priorities_2013.pdf



To provide context for this report, this section briefly discusses the current use of analytics/big data

and respondents’ evaluation of the potential future benefits. For more details on this and related

topics please refer to the full report, Big Data Priorities 2013.

Analytics in day-to-day business

QUESTION: To what extent do you use data analytics in everyday decision-making and

processes in your organization?

Just fewer than one-half of businesses (47.1%) use analytics in everyday decision-making and business processes today. These organizations use analytics at varying levels of intensity.

• 5.2% use analytics across the organization, and regard it as a core competency.

• 5% use analytics in most departments, 14.4% use analytics in a limited number of

departments, and 22.5% have just starting using analytics.

• A further 18.1% will deploy analytics capabilities in 2013, raising membership of the

analytics club to 65.3% of organizations.

• Organizations with 100+ staff are much more advanced on the analytics deployment

path.

Around one-half of businesses (52.9%) don’t use analytics in everyday decision-making and business processes today, but 18.1% plan to start in 2013.

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Note: This chart shows the use of analytics generally, irrespective of the method of producing the

analytics, or whether the underlying data sources are operational systems, data warehouses or

distributed data infrastructure such as Hadoop, Map Reduce or similar.

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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percentage currently using/not using Analytics/Big Data, n=596

34.7% 18.1% 5.2%22.5% 14.4% 5.0%

25.4% 15.9% 25.4% 21.6% 7.3%

4.3%

40.5% 18.6% 21.9% 8.6%

4.1%

6.3%

41.1% 22.1% 16.8%

2.1% 4.2%

13.7%Not Disclosed

<100

100 Plus

All Respondents

Org

aniz

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ize

(num

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of e

mp

loye

es)

We don’t use analytics in every-day decision-making processes

We don’t use analytics in every-day decision-making processes, but plan to do so in the next 12 months

We have started using analytics in every-day decision-making and processes, but it’s early stages

We use analytics in every-day decision-making and processes, but in a limited number of departments/business units

We use analytics in every-day decision-making and processes in most departments/business units

We use analytics in every-day decision-making and processes across the organization, and we regard it as a core competency in our business



The growing potential of analytics/big data

QUESTION: What is the potential for data analytics/big data to have a major influence on your

organization’s performance?

Organizations clearly see the growing potential of analytics/big data. The proportion that say analytics/big data will have a major influence on their business performance doubles from 2012 to 2014.

• Just fewer than one-

quarter of organizations

(23.8%) say analytics/big

data has high potential

to have a major influence

on their business

performance (rating 8 or

above on a 10-point scale)

• But that number grows to

37.1% when respondents

look a year ahead (2013),

and doubles to 50.3% when

they look ahead to 2014.

The chart shows the proportion of organizations rating analytics/big data potential at 8 or above on a

10 point scale (1=No potential, 10=Great Potential).

Larger organizations see greater potential in analytics/big data

• 30.6% of larger businesses (100+ staff) say analytics/big data has high potential

to influence business performance, compared to 20.4% of smaller organizations

(<100 staff).

• Organizations that did not disclose their size (and which comprise a mix of larger and

smaller businesses) are less bullish about analytics/big data, with 16.8% saying it has

high potential to impact their business.

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0% 10% 20% 30% 40% 50% 60%0% 10% 20% 30% 40% 50% 60%

2014

2013

50.3%

37.1%

2012 23.8%

Percentage Of Organizations Saying Analytics/Big Data Has High Potential, n=596



Analytics/big data produces measurable financial returns

QUESTION: To what extent has your organization achieved measurable financial benefits from

your data analytic/big data initiatives?

Almost all businesses say they derive measurable financial benefits from analytics/big data

• All but one-tenth

(9.9%) report achieving

measurable financial

benefits from analytics/

big data initiatives, but

the extent varies. Around

one-fifth (19.3%) have

achieved major financial

benefits, and 6.4% report

achieving financial benefits

to a great extent.

• One-third report they’ve

achieved financial benefits

to a minor extent, and

a further one-third to a

medium extent.

Not Disclosed

<100

100 Plus

All Respondents

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

21. No Potential

19.0% 10.1% 7.9% 6.0% 14.3% 8.4% 10.6% 8.4%

3.7%

23.8%

11.7%

12.1% 9.1% 7.8% 6.5% 12.5% 9.1% 12.5% 10.3%

3.9%

16.4%

20.8% 9.7% 9.3% 6.7% 15.6% 9.3% 8.2% 7.4%

3.0%

10.0%

30.5% 13.7%

4.2% 3.2%

14.7%

4.2%

12.6% 6.3% 5.3%5.3%

Percentage Rating the 2012 Business Potential of Data Analytics/Big Data, n=596

10. Great Potential3 4 5 6 7 8 9

30.6%

20.4%

16.8%

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(num

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0% 10% 20% 30% 40%

To a great extent

To a major extent

To a medium extent

To a minor extent

Not at all

Percentage Of Organizations Using Analytics/Big Data, n=233

9.9%

6.4%

19.3%

32.2%

32.2%

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Obstacles to maximizing benefits from analytics

QUESTION: Which of the following (if any) are the biggest obstacles to your organization deriving

maximum benefits from analytics?

Some organizations say they just don’t have an analytics culture, or they lack sufficient analytics skills and data skills. The two obstacles are closely related — without analytics skills it’s hard to influence and educate the senior leadership team about the potential of analytics, therefore it’s hard to embed analytics in the organization’s DNA.

• Lack of an analytics culture (stated by 20% of organizations), and lack of skills in

the area of analytics/data/data science (16.3%) are the two biggest obstacles to

organizations deriving maximum benefit from analytics.

• Lack of skills in analytics/data/data science is a critical topic that has been discussed

widely over the past year or two. McKinsey Global Institute’s June 2011 report, “Big

data: The next frontier for innovation, competition, and productivity,” was instrumental

in publicizing this issue. That report says an extra 140,000 data science professionals

and up to 1.5 million data-savvy managers are required for the US economy to take

advantage of big data’s potential.

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0% 5% 10% 15% 20%

None of the above

Inability to demonstrate the return on investment

Inability to prioritise funding for big data

Inability to agree ownership of data across the organization

Lack of senior executive leadership and support

Other initiatives are given funding priority

Lack of skills in the organization in the areas of analytics / data / data science

Lack of an analytics culture in the organization

Percentage Of Organizations Using Analytics/Big Data, n=270

20%

16.3%

12.6%

11.5%

8.1%

8.9%

8.9%

13.7%



Lack of executive leadership and support and an inability to agree on ownership of data across the organization are also preventing maximum benefits being realised from analytics.

• Disagreement about ownership of data is likely to result from another of the declared

obstacles – the lack of senior executive leadership and support. Where the leadership

is not engaged with analytics initiatives it’s likely to be tougher to win the executive

sponsorship that helps cut across organization silos to resolve issues like data

ownership and sharing.

Data issues are clearly prominent in the obstacles list, and a number are being addressed as

priorities.

Businesses are tackling a range of data issues

QUESTION: To what extent is your organization prioritizing the following data issues?

Organizations are attending to many data issues, from business-focused topics like creating confidence in the veracity of data to more technical ones like automating the extraction/transform/load (ETL) process, or policy issues like agreeing ownership and governance of data.

The priority data issues for around two-thirds of organizations are providing usable data to the business, doing so cost-efficiently, and within appropriate data security controls.

• 65.7% of organizations say providing usable data to business decision-makers is a top

or major priority, 65.2% say ensuring data privacy and security is a priority, and 59.6%

regard managing and processing data more cost efficiently as a priority.

• Creating confidence in the veracity of data and ensuring the timeliness of data also rate

as priorities for many organizations.

• These priorities are all business-focused issues, and suggest analytics-savvy

organizations are focused on increasing the value they provide to the business

through data.

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The next group of priority topics are broadly to do with sourcing and integrating data, and are priorities for over one-half of organizations.

• Integrating disparate sources is a top or major priority for 55.95 of organizations,

while automating the ETL process is a priority for 53.2%, and identifying new data

sources that can improve analytics outcomes is a priority for 52.4%. This latter priority

suggests organizations are looking outside for other data sources, as can be seen from

the use of social media data and DaaS providers described in the next section.

The remaining data priorities, mostly to do with data policy, have lesser focus but are still important for just under one-half of respondents.

• 52% say defining standards so that data across the organization is defined in similar

ways is a top or major priority.

• Agreeing on principles for sharing data across organizational silos is considered

a priority by 47.2% of respondents, and is closely related to another topic, that of

agreeing ownership and governance of organization data.

The

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Agreeing ownership and governance of organization data

Embedding data in the application to encouragebusiness users to regularly use analytics

Agreeing on principles for sharing organization across organizational silos

Defining standards so that data across the organization is defined in similar ways

Identifying new data sources that can improve Analytics outcomes

Automating the data Extraction / Transfer / Load (ETL) process

Integrating disparate data from sources across the organization

Timeliness (freshness of data at point of use)

Creating Confidence in the veracity of the data

Finding ways to manage and process data more cost-effectively

Ensuring data privacy and security

Making data available to business decision-makers in usable formats

Top PriorityMajor PriorityMedium PriorityLow PriorityNot a Priority

10.0%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percentage of Organizations, n=233

6.9%

3.4%

2.1%

3.4%

2.6%

3.4%

3.9%

3.4%

3.4%

5.6%

6.9%

6.4%

4.3%

24.9% 33.5% 32.2%

6.9% 24.5% 25.3% 39.9%

12.4% 25.8% 36.9% 22.7%

10.7% 28.3% 32.6% 24.9%

9.9% 30.9% 31.8%

7.3% 34.3% 36.9% 18.0%

9.9% 33.0% 33.5% 19.7%

15.5% 28.8% 30.9% 21.5%

12.0% 31.8% 30.5% 21.5%

14.2% 33.0% 32.2% 15.0%

14.6% 32.6% 29.2% 16.7%

17.6% 32.6% 24.9% 18.5%

24.0%



Types and sources of data used for analytics

Question: Which types and sources of data does your organization use for decision-making on a

day-to-day basis?

While analytics-using organizations are almost twice as likely to use internally-sourced data as they are to use data from external sources, adoption of the latter has grown rapidly.

• More than three-quarters of analytics-using businesses (77.4% ) source data from

systems like Finance, Enterprise Resource Planning (ERP), Customer Relationship

Management (CRM) for use in day-to-day decision-making.

• By contrast around one-third (34.4%) are using data sourced from social networking

and media. Given the relatively recent development of social media this is a relatively

high adoption, and if it continues it will quickly become a widespread practice.

Traffic and activity on an organization’s own website is also an important data source on which analytics is performed.

• Almost one-half (44.8%) use data generated from internet inquiries, purchases etc.,

and 27.4% use clickstream data showing where visitors spend time on their site.Businesses use a variety of data sources for day-to-day decision-making. Much of that data comes from internet-initiated events.

• All Analytics-using businesses use operational applications data every day, no exception.• Over one-half (57.9%) use data generated from internet enquiries, purchases etc, and 35.4% use clickstream data showing where visitors spend time on their site• Over one-third (37.3%) use data from sensors (i.e. machine-to-machine data), and 34.4% use data supplied by commercial 3rd party Data as a Service (DaaS) suppliers• Almost one-third (30.6%) also use data from mobile devices

Operational Data e.g. from Finance, ERP, CRM and other internal applications

None of the above

Mobile Devices, location data e.g. smartphones, tablets

Internet transactions data e.g. from purchases, inquiries, requests etc.

Social Networking and Media e.g. tracking and analyzing social media updates, tweets, blog posts

Networked Devices and Sensors – e.g. electronic devices such as IT hardware, smart energy meters, temperature

sensors, chips in products etc.

Data as a Service (DaaS) i.e.the aggregation,integration, automation and dissemination of 3rd party information from suppliers such as

StrikeIron, Experian,TheWebService, Dun & Bradsteeet, Data.com etc.)

0% 10% 20% 30% 40% 50% 60% 70% 80%

Percentage of organizations disclosing, n=209

Internet Clickstream data e.g. analyzing where visitors go on your website

77.4%

44.8%

34.4%

28.9%

27.4%

26.7%

23.7%

6.3%

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The emergence of sensors as a major data source attests to the growth of the machine-to-machine (M2M) ecosystem.

• 28.9% of organizations that use analytics source and analyze data from sensors (e.g.

electronics embedded in products, smart energy meters etc.)

• A separate research study by ZDNet on M2M published in Jan 2013 supports this

finding, showing 29% already use M2M or are implementing it now, and a further

14.7% will implement it in 2013.

Businesses also source and buy data from commercial third-party data suppliers, a practice that is becoming known as DaaS, and it’s a practice that will increase.

• More than one-quarter (26.7%) use data supplied by commercial third-party DaaS

suppliers such as Experian, StrikeIron, Dun & Bradstreet

• An accidental omission in this survey is a question on the sourcing of data from

government organizations. This is becoming widespread in a number of countries and

is a part of open government initiatives. Some of the data provided by such public

sector organizations (e.g. population and financial data) is an important source for

businesses.

Mobile devices are another important data source – almost one-quarter of businesses (23.7%) use data from mobile devices.

Data-as-a-Service Providers (DaaS)

QUESTION: Do you use, or do you plan to use services from any of the following Data-as-a-

Service (DaaS) vendors to help solve your big data challenges?

The use of data from DaaS providers will double by the end of 2014.

• Analytics-using respondents say they will double their use of DaaS providers over the

next two years, indicating this will become an increasingly important source of data.

And as the number of analytics-using organizations grows, so will the use of DaaS. For

example, 18.1% of respondents say they’ll start using analytics in day-to-day business

during 2013, and 22.5% had just started using analytics in 2012. The combination of

these two (40.6% of organizations) will swell the use of DaaS.

• Of the organizations that currently use DaaS, 61.5% use at least two DaaS suppliers,

while 26.4% use at least three suppliers. Just 38.5% have a single DaaS supplier

suggesting that once an organization starts using DaaS they become aware of the

possibilities and build on that initial use by sourcing further data from other vendors.

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Dun and Bradstreet is the go-to source for DaaS, followed by Experian and InfoUSA.

• The one-quarter (26.7%) of organizations using DaaS providers employ a range

of sources. Currently, their number one supplier is Dun and Bradstreet (18% of

organizations use this source), followed by Experian (15%) and InfoUSA (9.9%).

Organizations that use DaaS providers report greater financial benefits from analytics/big data initiatives.

• 37.9 % of DaaS users say they’re achieving financial benefits to a great extent or a

major extent, while the figure for all respondents is 25.7%. It’s likely the use of DaaS is

one indication (among several) of a more sophisticated approach to analytics, so it may

be just one factor (rather than the only factor) that is contributing to the difference in

outcomes.

StrikeIron

TheWebService

Data.com

InfoUSA

Experian

Dun and Bradstreet

Already useIn next 12 monthsIn 1 to 2 yearsNo plans

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percentage of those using Analytics/Big Data, n=233

84.1% 5.6% 5.6%

4.7%

79.4% 6.0% 9.4%

76.0% 8.6% 7.3% 8.2%

77.3% 7.3% 5.6% 9.9%

70.0% 6.0% 9.0% 15.0%

67.0% 8.2% 6.9% 18.0%

5.2%

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Sur

vey

Met

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logy

Approach and sample

This is a quantitative survey based on a sample of US and Canadian organizations. The sample is

principally drawn from the database of opt-in registered members of CBSi’s leading business tech

media sites ZDNet and TechRepublic. A portion of the sample was generated from advertisements

on ZDNet and TechRepublic to capture the views on the audience who are not registered members.

The fieldwork for this report was conducted in the US and Canada.

The survey generated 1268 responses. After quality assurance and removal of incomplete surveys,

596 responses were sufficiently complete and included in the analysis. The sample size for each

chart in this report is displayed, and sample size varies due to the conditional path respondents

took through the survey. The initial questions about strategic perspectives on analytics/big data are

reported based on the full sample of 596 organizations.

A substantial number of respondents answered all key questions in the survey, but declined

to disclose details of their organization size, industry sector, and other information that could

uniquely identify them. This is understandable given many analytics/big data projects are critical

components in building competitive advantage. These responses are included in the survey, and the

organizations are identified as “Not Disclosed” in results reported by organization size and industry

sector.

The first branch in the survey separated respondents into those who use analytics in everyday

decision-making (281 respondents), and those who don’t (315). A second branch distinguished

between organizations using analytics/big data technologies and those who don’t. The latter group

were served one further question — about why they do not yet use analytics/big data. The former

group were served a range of questions on the following topics; their current use of analytics,

including targeted business outcomes; the roles that manage analytics/big data plans and budgets;

the data types and data sources they utilize; and the technology infrastructure they’ve deployed to

support their analytics/big data initiatives.

Scope and Terminology

The Big Data Priorities 2013 survey was focused both on analytics and big data. This was a

deliberate attempt to better understand the overall scope and direction of all analytic initiatives in

businesses. In most cases, questions asked broadly about approaches to analytics/big data, but in

limited cases questions were asked more narrowly about analytics or about big data.



Timelines

The project spanned the following major activities:

Respondents

The questionnaire was targeted at organizations with a minimum of 100 employees, but a

substantial quantity of responses came from smaller businesses via the advertisements on ZDNet

and TechRepublic. Due to the obvious interest in the topic from these organizations, and their

initiatives to utilize analytics/big data, these responses are included in this report. In most cases

their answers are reported separately from larger organizations and those that did not disclose

organization size (which ZDNet interprets from answers to the survey are a mix of small and large

businesses).

Respondent Demographics

Respondent Organizations – by Size

Project design, including scope and questionnaire design

August/September 2012

Fieldwork October/November 2012

Analysis and reporting December 2012

Webcast to launch the findings January 24, 2013

<100

100+

45.1%

15.9%

38.9%

Not Disclosed

n=596

Sur

vey

Met

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Respondent Organizations – by industry sector

0% 10% 20%

Not Disclosed

Other

Transportation/Aerospace

Engineering/Construction/R&D

Media/Entertainment/Design

Retail/Distribution/Wholesale

Manufacturing

Banking/Financial Services/Insurance etc

IT and Communications

Business Services/Consulting

Education/Health Care/Government

Percentage Of Organizations, n=596

15.8%

2.7%

3.9%

4.5%

15.1%

15.9%

5.7%

6.7%

7.0%

9.2%

13.4%

Sur

vey

Met

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Documents

Big Data Priorities 2013 - images.insight.dnb.comimages.insight.dnb.com/...BigDataPriorities_Custom... · MapReduce and advanced analytics tools first deployed at leading online businesses