Big data cannot be processed with traditional analytic tools because of its complex and fragmented nature. For this reason, decision-makers must develop an innovative strategy for tackling big data, as conventional methods are no longer applicable.
This was highlighted in a recent report by Information Management, which said decision-makers need to implement tools that take volume, velocity and ambiguity out of the equation without sacrificing
data quality. In many cases, the biggest challenge associated with big data is that the wide variety of information can be processed multiple ways. As a result, executives need to define and classify resources based on established parameters that meet an organization's unique demands.
Information Management said companies will also need to use taxonomies, ontologies and semantic libraries to analyze content derived from metadata. In doing so, organizations can improve data quality.
A separate report by IT Business Edge said decision-makers should keep end goals in mind during big data projects, as employees can easily be distracted by the massively diverse volumes of information associated with the initiatives. By addressing big data with unique strategies, companies will likely be able to experience more success from the programs.
