Falling in love with Big Data already? Great! But, just as any relationship requires, you have to also deal with the downside, even as you enjoy all good stuff. The Big Data explosion and its emerging market is undoubtedly one of the most discussed now, within the tech community. Different platforms, different facets of businesses, different organizations in varied regions—the presence of Big Data is overwhelming. It has immense potential to drive business intelligence through customer analytics and understand the life cycle of customer experience.  But when we talk of Big Data we are not only talking about massive volume, we also have to consider things like velocity and variability. Along the lines of these characteristics are inevitable challenges that will hurdle the emergence of the Big Data industry as a whole.

The first set of obstacles facing Big Data are integration, mining and utilization. Associated with integration issues are legacy systems, unique formats and incompatible standards. To address these, companies need to have a solid and robust integration plans that are focused on real-time and high frequency scale. Further enhancing technologies to tackle Big Data hurdles will bring forth new business, thus new jobs.

Chief Marketing Officer at Syncsort, W. Sean Ford talks about how present tools are “not meeting” the big demands: “Organizations are struggling with how to strike a balance between expensive and time-consuming workarounds for dealing with exploding data volumes, and aou SVR n jxc   desire to drive ever-increasing value and insights from this data. Despite the significant investments that businesses have made in acquiring and managing their data integration tools, this new survey data clearly shows that the majority of tools are failing to keep up with today’s requirements from both a technical and economical perspective.”

Other impediments, like having an extremely complex development model such as Hadoop Apache, requires specialized developers to understand how to break the problem down into little pieces and have it ready for treatment via a complex architecture. Perhaps a dynamic schema revolution is something that would benefit unstructured data developers. Competition is also a good way to deal with this kind of intricacy.

One obstacle that could be really challenging and outside the tech community jurisdiction, are federal regulations that could hamstring the innovation plans for Big Data and analytics. Striking a balance is the goal of these laws and making sure that customers have the knowledge of how sites use their data.

The revelation of various challenges surrounding Big Data and technologies linked to it is actually a good sign. This only means that attention is now shifting to this industry, and more and more experts are providing valuable input that would be useful to both established organizations and startups that are presently working on the potential of Big Data for their own purposes.