Data Collection Methods for Big Data

Big data has been a topic of much discussion recently. Some see it as a threat to the privacy of individuals, while others welcome it as a way to improve business. While there is some gray area when it comes to how much information can truly be collected, there is no doubt that the ability to collect massive amounts of data is changing the way companies interact with their customers. Below are some of the primary areas where big data is impacting organizations today.

how is big data collected

Big data sets like customer satisfaction surveys, loyalty rewards programs and the buying decisions made by human beings are being collected for different reasons. Large data sets, like those gathered during customer satisfaction surveys, help marketers understand their customers’ needs and concerns. Similarly, big data sets that are collected through social media marketing campaigns help product developers understand their target audiences and devise strategies to make their products more appealing.

Big data sets have even more applications. Like any other form of big data, the accuracy and veracity of the data collected depends heavily on how it is analyzed. One challenge is determining the veracity of results. Some researchers collect data sets and analyze them over again to identify trends or patterns. However, if these patterns are not significant, it may be very difficult for a company to make massive changes to its production process or business structure.

Another challenge faced by companies like Yahoo! or Facebook is the problem of inconsistency or inaccurate measurement. For example, when a person performs a search using Yahoo! or Facebook, the results displayed may not always be the same for different individuals or different companies like Yahoo! or Facebook.

Another area where big data analysis has an impact is in the area of salary setting. Companies are able to collect large amount of salary information from employees and use this information to create pay tables, which are then utilized to calculate employees’ salaries. However, the accuracy of these calculations is questionable. As there are no formal statistical methods employed by companies to arrive at salary figures, the estimates generated may be inaccurate.

Perhaps the biggest problem faced by most businesses today is fraud. While it is relatively easy to commit fraud online, such activities are much harder to do when conducting business over the phone or through the mail. In order to reduce this problem, many companies have decided to turn to big data collection in areas like fraud management and customer authentication. Many companies like Yahoo! or Facebook have already created internal departments focused on these issues.

In addition to efficiency, accuracy, big data sets can also help save money. Traditional data processing methods can be quite expensive and wasteful. Hadoop’s distributed data sets can free up a significant amount of resources that would have otherwise been spent in processing traditional data sets. This is particularly important for sales and customer service tasks. In a competitive marketplace, having the extra capacity available is critical.

With the rise of big data and its ever increasing capabilities, companies have come across new challenges and new opportunities. In the automotive industry specifically, the need for faster and more accurate analysis has created a need for data generated at a much quicker pace. Because of this, there has been a parallel increase in the use of mobile devices and mobile analytics devices to facilitate this process. Mobile devices allow for data generation to take place on the go, which increases efficiency and reduces costs. By taking advantage of this, car companies are taking advantage of a technology that is here to stay.