Five Positives and Five Negatives of Big Data in Our World Today
Big Data was coined in 2015 to mean a bulk of data. Data is used in every instance, from the medical field to the energy field to the Forex trading market, when you want to buy Iraqi dinar, and every industry in between. The volume of data has multiplied since then and cannot be handled by conventional data-handling systems. Therefore, it is still a new concept and, in this article, you should understand the elaborated uses of Big Data, its cons, and its pros in social life.
Contents
Advantages of Big Data: Big Data gives a competitive advantage to a business
Information is essential to the success of an organization actively operating on the market. Businesses need to get the right information and as fast as possible to their customers, shareholders, and partners. This has been a challenge for many companies because there is ample data produced on different platforms. Google alone receives up to 3 million search inquiries per minute. Big Data allows a business to get the right information to its parties, thereby giving it a competitive advantage on the market.
Big Data helps you to understand your customers better
Customer engagement is still recognized as a critical driver of the success of a business. But, despite that, multiple companies struggle to reach the goal. Even though the possibilities given by the digital landscape are endless, companies always find it daunting to utilize these opportunities in the best ways possible. Big Data helps businesses understand their customer better by providing detailed information regarding consumer preferences.
Big Data helps identify current trends
Big Data analytics entails examining large data amounts. It is done to uncover patterns and correlations while giving better insight into businesses. That way, business people can make appropriate decisions based on current trends.
Healthcare Big Data enables precision-medicine
Precision medicine is a treatment and prevention approach that considers individual variability genes and every patient’s personal lifestyle. The approach allows healthcare professionals to predict the right treatment strategy for a disease. Healthcare Big Data enables doctors to practice precision medicine using prescriptive analytics.
Big Data helps organizations to minimize hiring risks
Successful organizations know the value of hiring and maintaining top talent. Human resource departments leverage Big Data analytics to poach top performers before hiring. To deal with voluminous employees’ sets, human resource managers are embracing Big Data analytics to employ competent workers and retain them.
A challenge follows every opportunity. While Big Data has advantages, it also has the following disadvantages:
Disadvantages of Big Data: The need for talent
The success of Big Data analytics in the industry relies on data mining scientists and experts’ qualifications. These parties are coveted. They are also highly paid. The lack of a Big Data skillset has been a challenge over the past two years.
Possibility of failure due to privacy issues
Presuming organizations can keep data safe from cyberattacks; there is a possibility of misusing the information. The data can be used illegally. For instance, insurance providers impose premiums based on consumer behavior. Big Data makes it possible for companies to determine the future by invasive financial profiling in case of an accident.
Difficulty in mining the data
Big Data mining entails the extraction of valuable information from a set of data. It covers the classification and regression of data. Most data mining systems have failed to work well with Big Data because of the methods involved and the technological progress of mining data.
Mining from sparse
Big Data mining from sparse provides incomplete data. Scant information cannot be utilized in drawing a reliable conclusion. Therefore, common approaches employ dimension reduction while featuring selection to cut down the existing data dimensions and include generic data samples.
Advantages of Big Data: Data inconsistency
The initial phase of Big Data mining is data analysis. The data has to be well constructed. But given the different sets of drawbacks in Big Data mining and analysis, experts have the challenge of properly representing and accessing the constructed data for research. Information needs to be processed to improve results.
Social life is progressively occurring in different digital environments. Digital systems mediate it. Consequently, Big Data represents the information generated by the digitalization of life. These segments involve digital life, digitalized life, in addition to digital traces. There is significant potential in applying Big Data to analyze a different phenomenon that is difficult to observe. But some vulnerabilities need to be addressed.
