Big Data Analysis
“Big data, big data, big data.” If you’ve spent any amount of time on social media lately, you’ve most likely seen an article (or 10) about big data. While people are starting to grasp the power of what big data analysis brings to the table, many are still unclear on how to make it a reality. What’s holding us back?
Current Big Data Obstacles
The tools for big data analysis are still in their infancy (in my opinion), so naturally the big data analysis process will only continue to develop and improve. The real obstacle that needs to be addressed is how do we learn to ask the right questions? Unless you’re a “data steward” or a data systems administrator who knows the data inside and out; understanding which questions to ask in the analysis can be challenging. Big data analysis needs to become an easier process before it becomes valuable to the masses.
Getting Over The Hump
Before someone learns how to ask the right questions, they must first have the motivation to ask the question in the first place. So how do you provide motivation? I think the long-term motivation comes from seeing the power and end results of a big data analysis. Once someone sees the whole process from start to finish, they’ll begin to question alternatives.
One of the big challenges in the big data phenomenon is getting people to think a certain way or understand how to solve a problem. This is something that will need to be addressed at an early stage in the educational process. We all had to do a science experiment at some point in school growing up. Perhaps the educational curriculum could begin to include simplified big data analysis experiments?
Big data analysis software and tools will continue to develop and improve as expected, but the real challenge lies in education and a shift in thinking. For big data analysis to become a solution to the masses, there needs to be an easier way for people to know what questions to ask, uncover new relationships, and tell stories with the data.
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