Big Data Means Big Prospects for the Channel

Big Data Means Big Prospects for the Channel

1-Does Your Organization Have a Big Data Initiative Under Way?Does Your Organization Have a Big Data Initiative Under Way?

The vast majority are in some stage of big data deployment. Yes, operational and in production: 32%, Yes, under consideration: 31%, Yes, completed: 28%, Nothing planned: 9%

2-Big Data BudgetsBig Data Budgets

Within three years, 50% say big data budgets will exceed $10 million. 2013: Greater than $1 million:68%, Greater than $10 million:19%. 2016: Greater than $1 million:88%, Greater than $10 million:50%.

3-Business Functions That Drive Big Data InvestmentsBusiness Functions That Drive Big Data Investments

Line-of-business executives and risk officers are leading the charge. Sales/marketing: 70%, Risk management/fraud/security: 68%, New-product development: 64%, Research: 64%, IT and operational: 64%

4-Big Data Initiatives in Which Investments Are MadeBig Data Initiatives in Which Investments Are Made

Analytics applications and data integration top the list. Acceleration of analytical processes: 70%, Development of more sophisticated analytics: 70%, More effective integration of existing data sources: 69%, Creation of analytic sandboxes for data discovery: 65%, Migration of batch processes to big data: 57%, Improved fraud detection: 54%, Deployment of advanced analytics: 53%

5-Primary Business Benefits ExpectedPrimary Business Benefits Expected

It’s also about bigger, better and faster data. Accelerate speed at which insight Is gained: 87%, Integrate a greater variety of data sources: 82%, Analyze larger volumes of data: 81%, Improve overall analytics capabilities: 80%, Analyze new sources of information in real time: 70%, Reduce the cost of the analytics application environment: 70%, Offload production systems: 62%

6-Was an ROI Analysis Required to Get Big Data Project Funding?Was an ROI Analysis Required to Get Big Data Project Funding?

No, it’s a long-term strategic initiative: 50%, Yes, based on revenue, growth and savings: 20%, Yes, based on cost savings: 10%, No, ROI justification is not required in their organizations: 8%, No, for other reasons: 7%, Yes, ROI based on revenue growth: 5%

7-Factors That Drive Big Data AdoptionFactors That Drive Big Data Adoption

Executives are aligning big data projects to business objectives. Executive sponsorship: 83%, Clear definition of business objectives: 82%, Recognition of data as a shared asset: 68%, Consensus on importance of analytics: 65%, Enterprise information strategy: 64%, Organizational alignment: 64%

8-Steps Taken to Ensure Successful AdoptionSteps Taken to Ensure Successful Adoption

Establishment of governance standards: 61%, Establishment of executive oversight committee: 56%, Establishment of big data lab or center of excellence: 52%, Designation of line-of-business project owner: 49%, Designation of C-level executive as owner: 49%

9-Does Your Organization Have a Chief Data Officer?Does Your Organization Have a Chief Data Officer?

The study suggests it’s a job description that’s still evolving. No: 52%, No, but considering: 21%, Yes, within the last three years: 17%, Yes, within the past year: 7%, Yes, prior to 2010: 2%

10-What Is the Business Value of Big Data?What Is the Business Value of Big Data?

It takes the guesswork out of business. Better fact-based decision making: 80%, Discovery of new correlations and patterns: 74%, Reduced risk: 70%, New-product innovations: 66%, Improved customer experience: 66%, More efficient operations: 64%

11-The Primary Drivers of Big Data ProjectsThe Primary Drivers of Big Data Projects

Integrating and analyzing data from existing sources: 86%, Integrating and analyzing data from new sources: 83%, Integrating and analyzing larger volumes of data: 80%, Ensuring greater accuracy: 65%, Integrating and analyzing streaming data: 55%

12-Big Data or Database Management Solutions Under EvaluationBig Data or Database Management Solutions Under Evaluation

Hadoop still dominates the conversation. Hadoop: 63%, Teradata/Aster: 43%, Cloudera: 36%, IBM PureEdge/Netezza: 33%, Oracle/Exadata: 29%, Microsoft SQL Server: 29%, EMC Greenplum: 24%

13-Analytics or Visualization Tools Under EvaluationAnalytics or Visualization Tools Under Evaluation

Relative newcomers have a strong presence. SAS: 77%, Tableau: 63%, SAP Business Objects: 52%, Microstrategy: 41%, Qlikview: 30%, Revolution Analytics: 28%, Tibco Spotfire: 24%

14-Data Domains of Most InterestData Domains of Most Interest

They are usually the areas that are the most opaque. Customer transaction data: 82%, Financial data: 75%, Market data: 68%, Social media data: 65%, Behavioral data: 65%, Fraud detection: 61%, External data sources: 61%

15-Respondents' Big Data Talent RequirementsRespondents’ Big Data Talent Requirements

Retraining is preferred to recruitment. Need to invest in retraining: 68%, Combine retraining with recruitment: 46%, Actively recruiting data scientists: 30%, Have successfully recruited data scientists: 30%, Face extreme challenges recruiting talent: 21%, Have enough in-house expertise: 19%, No need for data scientists: 4%

Michael Vizard
Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a contributor to publications including Programmableweb, IT Business Edge, CIOinsight, Channel Insider and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.


Must Read