Surveys that show CIOs dislike big data are wrong. There are bigger reasons for IT to resist taking on another disruptive technology.
Part of the reason may be that large companies are fundamentally unprepared to deal with the collection, storage, and use of giant databases, according to a study released Monday by revenue-management application vendor PROS.
The company surveyed more than 100 aftermarket parts-manufacturing companies. It found 65% not only found themselves unable to deal with the complexities of big data, but named that inability as their leading challenge.
Some of the problem is technological--the pricing and marketing managers most likely to benefit from big data prefer to work on spreadsheets or other apps that can't handle either the volume or complexity of analyzing big data sets, according to Patrick Schneidau, VP of product marketing at PROS. Sixty-two percent of respondents said they rely too much on spreadsheets to give them up; half said spreadsheets are the only app they use to calculate or set prices.
Justifying the cost of a big data project requires that end users be actively interested in pursuing one, which just wasn't the case in most of the 255 companies surveyed, Coulter said. Only 21% of companies had deployed any big data before 2012, the survey showed, while 7% plan to continue using it past 2013.
Rather than chase big data as a way to identify new customers, new opportunities, or better data to support pricing decisions, respondents said the main targets for their storage spending were:
-- To support server consolidation and virtualization;
-- To meet increased needs of existing business applications;
-- To overcome poor archiving practices now or in the past;
-- To support new business apps; and
-- To improve disaster recovery and the retention of backup data.
Those big data luddites may be shooting themselves in the foot, however, according to the Information Security Forum, which issued a report Wednesday showing analysis of big data that lists threats, risks, and security incidents can cut overall security risk by identifying the most serious security risks, rather than those that simply get the most attention.
Most companies analyze security data to identify threats, but only 20% analyze incident data to improve security or performance by identifying data that is the subject of the most (legitimate) requests for information. These early alerts most likely to lead to hardware failures or identify threats or penetration techniques might be undercounted as serious threats to overall security.
Weakening the appeal of big data is the increasingly intense fear among senior-level IT managers that their companies' most valuable data is vulnerable to loss or corruption during disasters, according to a survey from big data management vendor Quantum.
According to Quantum's 2012 IT Manager Survey, 90% of IT decision makers worry they will lose data during disaster-recovery operations--an increase of 3% over last year.
The most common disasters are virus attacks, operating system failures, and problems with data archives, rather than the traditional fire/flood/natural disaster scenarios for which most disaster-recovery plans are designed.
The overall picture is of a market divided--between IT executives optimistic about the benefits of more analysis versus those who think big data will lead to big problems, and also between business unit executives who see the potential in ever-more-granular knowledge of customer motivations versus IT executives exhausted by virtualization and cloud projects who resist leaping into a third new technology with the potential to fundamentally change the way IT does its job," Castro said.
"There are a lot of problems and risks with big data that are just extensions of risks IT has always dealt with," Castro said. "You have to know where the information is coming from, the policies of the provider, whether the data is being backed up, where the information is and who has access to it--all the questions CIOs ask about new technology, but haven't had time to get answers yet."
The Agile ArchiveWhen it comes to managing data, donít look at backup and archiving systems as burdens and cost centers. A well-designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems.
2014 Analytics, BI, and Information Management SurveyITís tried for years to simplify data analytics and business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.