Big Data Integration, Management Challenges Linger
The hype surrounding "Big Data" and all its glory is appealing to companies of all sizes, encouraging decision-makers to build projects as soon as possible. Although properly executed Big Data initiatives will often enable firms to reduce costs, augment operations, and take steps toward meeting customer demands on multiple levels, poorly launched endeavors won't deliver the same results.
In many cases, the need to implement Big Data projects often outranks the planning that goes into those programs, causing firms to experience more management problems than necessary -- all of which prevent the initiatives from introducing substantial benefits. A recent study by Kelton Research on behalf of TeamQuest highlighted these challenges, noting that companies often experience problems associated with integrating, managing, and analyzing the substantial volumes of information that come into their possession thanks to Big Data.
Although the survey found that approximately 80 percent of IT decision-makers use capacity management tools to improve their Big Data projects, many firms are still encountering issues that inhibit them from prospering as much as they'd initially believed they would. This result is primarily due to the fact that a large portion of the business world is still not mature regarding their use of Big Data management solutions.
Addressing Big Data complexity
TeamQuest revealed that the biggest problem organizations have with Big Data is that they simply can't process information fast enough to meet their employee and customer needs. The sheer volume of resources being collected puts a strain on internal networks, creating more traffic and slowing operations.The survey also found that integrating data from various sources, managing the massive volumes of information, and maintaining system reliability are also major issues organizations are facing when embracing Big Data.
"Proper and mature capacity management tools and processes help organizations maximize the performance of their Big Data environments," said Scott Adams, director of product management at TeamQuest. "The smart organizations are using capacity management tools to get the most from their Big Data implementations and the more mature organizations are realizing the benefits."
How to approach Big Data
Before organizations jump into Big Data initiatives, executives should consider their problems beforehand, according to a Smart Data Collective report. By taking this approach, decision-makers can isolate their issues and customize data analytics and similar programs to help address those challenges.
At the same time, executives should take the size of their companies and the volume of data under their control into account. Although Big Data is agnostic in the sense that virtually any business can embrace the initiatives, some of the analytic, storage, and management tools may be financially out of reach or too complex for smaller, less-experienced organizations.
In many cases, cloud computing technologies can provide decision-makers with a scalable, cost-effective environment that makes managing capacity and traffic less complex. Because these are among the chief issues companies face when launching Big Data initiatives, the cloud may provide a viable option for any firm, regardless of size or stature.
As the business world as a whole prioritizes information management, analytics, and integration, forward-thinking executives need to consider how launching a Big Data initiative will impact their current and long-term operations. Although becoming a data-driven enterprise is on the list of goals for most firms, simply implementing a Big Data project without careful planning won't deliver the benefits decision-makers are looking for. Businesses need to plan ahead and calculate how to address the changes Big Data brings.
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