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Speed, Accuracy More Important than Volume for Big Data

November 15th, 2013 by - 6,325 views

Although information has always had an important role in the business world, the Big Data movement has placed a larger emphasis on the aggregation and management of digital resources. Companies around the world are now seeking programs that help employees collect and store increasingly larger volumes of information because most decision-makers believe the chances of striking gold will increase if they have more data to analyze.

Speed, accuracy more important than volume for big data

Speed, accuracy more important than volume for Big Data

Ironically, organizations that believe in collecting massive amounts of information often find themselves inundated by the sheer size of the resources under their control and, as a result, encounter new performance obstacles that lead to substantial issues. This conundrum is forcing executives to ask, “Is bigger always better?”

The answer is no, especially in today’s Big Data world. Rather than focusing on the quantity of information they collect, organizations should focus on the quality. Because there’s no finite definition for “Big Data,” each company is forced to develop its own innovative strategy that aligns with the way employees work on a daily basis. In many cases, speed will outweigh a number of other metrics associated with the information being collected. If an organization has the power to quickly convert unstructured data into useful insight for its marketing and sales teams, for example, it will likely be able to reduce client churn and improve its ability to attract, engage, and retain customers.

Still, many experts believe that the data with the largest business impact is the most difficult to measure. The need to do so will pressure executives to build robust warehousing environments that can make sense of various information sets as quickly as possible, allowing firms of all sizes to use a broad range of information for numerous practices, improving their ability to compete and prosper in the long run.

Quality over quantity
Of course it will become increasingly difficult to find a needle if the haystack continues to grow in size. This prospect should encourage executives to build programs that regularly maintain the haystack, trimming the unnecessary heaps of hay to make sifting through the pile less complex. In terms of data management, this means that organizations need to understand the complications and opportunity costs associated with the inability to keep information storage environments in check.

Because there is no single best practice approach to Big Data, it will be up to decision-makers to determine how much they emphasize accuracy and timeliness within their initiatives. For the most part, hiring new employees who have the skills to quickly and efficiently sort through large volumes of information is a good place to start because having the proper workforce is the best building block for a strong and comprehensive Big Data strategy.

In addition to people, organizations need to take the time to find the right technology to manage Big Data. Cloud computing can be a boon for firms that need a highly flexible and elastic infrastructure, while deploying sophisticated analytics solutions can help individuals quickly assess and evaluate the usefulness of the information at hand.

As the business world becomes increasingly competitive, decision-makers must develop Big Data strategies with speed and accuracy in mind. Simply adopting a policy that encourages employees to collect as much information as possible can be dangerous, especially when organizations don’t have the necessary skills and technologies needed to maintain those volumes. In the era of Big Data, quality will always reign over quantity because useful information will provide companies with more opportunities to improve operations, reduce costs, and augment the customer relationship landscape.

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The GoGrid Team is committed to bringing you the information, advice, and tools necessary to easily evaluate and deploy a broad range of Big Data technologies and maximize your infrastructure to meet your specific needs.

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