Never Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.
3 Big Data Pitfalls To Avoid
Frost & Sullivan urges big data neophytes to get professional guidance in order to avoid three common deployment mistakes.
February 5, 2014
11 Min Read
13 CIOs Share: My Big Mistakes
13 CIOs Share: My Big Mistakes (Click image for larger view.)
Big data presents big opportunities, but newbies may need experienced professionals in order to avoid three common deployment mistakes. Three of the most common problems in big data deployments are incomplete data collection, false starts, and disruptive drains on IT and data-professional staff productivity, according to a recent report by the research and growth-strategy consulting firm Frost & Sullivan.
In fact, these problems are so pervasive and the associated risks so great that organizations new to big data should seek out assistance from professionals -- whether technology integrators or big data consultants. Tapping professionals "can easily cost the organization less than doing the job in house," writes Jeff Cotrupe, author of Frost & Sullivan's "The World Moves Fast, And Data Is Driving" report.
[Want more on big data? Read "16 Top Big Data Analytics Platforms."]
The three traps the report describes have a corrosive effect, not only big data projects and teams, but also on the IT and business leaders who give such projects the green light, putting their credibility at stake. Here are the few of the risks inside each pitfall:
Failure to capture critical data. With haste and inexperience, you might miss relevant data that could illuminate revenue opportunities or ways to reduce customer churn. If competitors start taking advantage of what you miss, the entire business could be vulnerable.
False starts. Taking multiple shots at big data will delay implementation. The impact of any delay will only be magnified if competitors beat you to a breakthrough.
Resource drains. IT and data-management teams are under pressure to maintain daily operations, deliver new reports and analyses, and incorporate new capabilities. Overburdening employees with too many roles or short-staffing the day-to-day work is not the way to go. In fact, many successful practitioners report that their big data teams are quite separate from preexisting BI, data warehousing, and data management teams.
Underscoring the many technical considerations that go into a successful big data project, the report outlines a multipoint data-management model. There are considerations around everything from knowledge management, master-data management, and big data architecture, to data integration, data warehousing, and search, and to analytics, collaboration, and security and rights management. A confusing array of more than 300 vendors offers products addressing these areas, although 20 to 25 of the largest vendors are capturing the lion's share of big data spending.
"Those considering a big data initiative are ill-served if they simply follow industry buzzwords, listen to a favorite vendor or two, and then map out their data management strategy from there," Frost & Sullivan advises.
The report details a litany of potential big data payoffs in areas ranging from network optimization, product marketing, and mobile commerce, to customer-experience management, customer-profitability management, and revenue assurance. Focusing on the telco industry, the report observes that communications services providers, for example, are beginning to adapt mobile commerce processes, "not just for mobile advertising but to all customer communications, because it is as crucial to reach customers on the go as it is to help brands advertise."
Other big data plays include analyzing customer behavior and attributes against responses to questions and offers, and also identifying influencers and customers who are influenced, using social network analysis techniques.
If you're not sure where to begin with these sorts of analyses, the advice to seek help is worth listening to. There are many advantages to leaning on external experts to start, while keeping internal staff focused on current IT and data-management priorities. But more importantly, experienced hands with big data experience are better prepared to deliver a successful project, says Frost & Sullivan.
"From decades of experience optimizing IT infrastructures, and more recent experience implementing Big Data solutions, expert consultants understand where the vulnerabilities and risks are, and they plan accordingly," Cotrupe writes. "With proper upfront planning comes lower exposure to risk, decreased chance of unexpected disruptions, on-time project completion, and an agile business that seizes new opportunities instead of missing market windows."
As for those who insist on going it alone in the big data arena, perhaps the best advice we've heard comes from Scott Rose, VP of services at analytics consulting firm Think Big Analytics. "If you're going to be a pioneer," says Rose, "you better have some wilderness survival skills." In other words, don't expect quick wins.
Too many companies treat digital and mobile strategies as pet projects. Here are four ideas to shake up your company. Also in the Digital Disruption issue of InformationWeek: Six enduring truths about selecting enterprise software. (Free registration required.)
About the Author(s)
Executive Editor, Enterprise Apps
Doug Henschen is Executive Editor of InformationWeek, where he covers the intersection of enterprise applications with information management, business intelligence, big data and analytics. He previously served as editor in chief of Intelligent Enterprise, editor in chief of Transform Magazine, and Executive Editor at DM News. He has covered IT and data-driven marketing for more than 15 years.
You May Also Like