A growing number of organizations are jumping on the big data bandwagon, according to research from Gartner. Within the next two years, more than 70% of just over 300 survey respondents said they will invest in the technology. The figure represents a nearly 10% upswing from last year.
While the notorious three Vs: Volume, variety, and velocity have plagued most who attempt to wrangle loads of data, survey respondents paid the most attention to volume, that is the sheer amount of data.
Even though certain types of information have been gathered for quite some time, the quantity of that data has rapidly risen. If not properly managed, the structured or unstructured information that was once a profit point could turn into a costly, headache-inducing problem.
The research points out that data variety, the different types of information, can be one of the more problematic areas of big data to manage. With the upswing of social media, for example, a new set of skills and tools, plus expanded storage, is needed to make use of the information.
That may explain why more organizations aren’t attempting to get information from log data, often derived from social media. The survey revealed that the number of organizations attempting to glean insights from profiles and interactions dipped 2%. Gartner believes issues integrating social media with other data may be the root of the trend.
Figuring out what to do with, and how to manage big data from social media, isn’t the only problem IT professionals are facing. Mobile devices are also a pain point for developers as needs and goals can vary depending on the application’s target audience.
Despite the problems big data can present, the opportunities to extract valuable information cannot be overlooked. Given the uptick in organizations planning to deploy a big data project in the near future, it seems business leaders are getting the picture. Now it’s up to IT professionals to figure out how to deal with big data in a cost-effective and timely fashion.
Has your organization struggled to integrate information gathered from new sources, such as social media, with more traditional big data sources? How have you gone about overcoming the obstacle?