The importance of finding relevant data

Posted by Justin Hesser on September 24, 2013

As the quantity versus quality debate continues to dominate big data discussions, it's important for information managers to take time to evaluate what separates the good from the bad. We all want good information, but which metrics do we use to determine the quality of our data? Perhaps the most important is relevance.

In the big data era, it has become increasingly common to sift through line after line of information to find exactly what we are looking for. We need data that's relevant to whatever task we are trying to complete. A social media marketer working on a Facebook campaign might not be interested in how consumers are behaving on Twitter, at least for the purpose of completing the task at hand. Determining productivity at branch A will require all information pertaining to that particular branch, and any data related to branch B will not help for this particular purpose. 

When relevant information is easy to be found, it can quickly be applied to the task at hand, improving operational efficiency and overall productivity. This was addressed in a recent article in the online publication Human IPO. Ayanda Dlamini, business development manager of LGR Telecommunications, spoke with the news source about the act of finding relevant information and the difficulties an organization can encounter when managing seemingly endless volumes of data. 

"Big data management is about managing the growing volumes, variety, velocity and complexity of global data to determine what customers are saying now, how market sentiments are changing, and how the business should react," Dlamini said. "Trends are key to understanding customer behavior effective use of big data depends on finding the now in structured and unstructured data."

While we know it's important to weed out irrelevant information and focus only on the data that can be directly applied to what we're doing, the question is, how do we do this in a quick and easy manner? This might not be accomplished via traditional technology, so custom FileMaker development is an ideal solution. Using the platform to develop a custom database software system can give users the ability to monitor information and sort it according to relevancy. This reduces time spent searching through massive quantities of irrelevant data and can significantly improve a number of business processes.