What’s not so great about Big Data?
The craze that the big data instills with the world of today is magnum. The purpose that the big data serves has become the very reason behind it becoming indispensable nowadays. With digital transformation on a high tide and artificial intelligence shadowing every arena of our activities, big data acts as a supporting arm for the two. Big data refers to the sets of large data, which subject to analysis and mining uncovers certain trends, behaviors, patterns, etc. Big data enables the owners of the same to unveil even the minutest of details from buying and eating habits of their customers to even their behavior and the reasons behind it.
Big data is also becoming famous in the field of research and policymaking. Companies, organizations and even government centers are increasingly relying on the availability and use of big data. The mere fact that we are able to collect and manage such a huge repository of data in relation to human activities and can bring out the trends and patterns of their behavior has pushed the human civilization one step further. Big data has opened doors to many new opportunities, for not only new jobs and careers but also for the betterment of society.
But there exist certain basic problems while dealing with big data which are discussed in brief below:
v Accessibility Issues: Availability of big data becomes an issue as collection and management of such a magnum database requires expensive infrastructure and resources which is not possessed by every organization or individual. Accessibility thus becomes a hindrance when it comes to dealing and working with the help of big data. Other than collecting one’s own big data, the purchasing of databases becomes the next option. The purchase of big data from the sourcing (collecting) organization is again a very expensive proposition. Very often even the purchasing option is not available with the organizations (buyers of big data) due to privacy reasons. The collectors and managers of big data take great care and caution while dealing with the data of their clients and therefore do not sell the data even for consideration. A great example to explain this is social media like Facebook, Instagram who are bound by their privacy norms to maintain the utmost security of the data produced by its users. Another example would be the data of the patients managed by the hospital administration, which again is inaccessible for other organizations. Thus accessibility of big data is questionable, therefore, restricting its use the purpose of research and policymaking.
v Dynamic Nature of the Data: With the human civilization moving at the speed of light, the trends and behavior patterns are also constantly changing. The big data is collected at a given period of time and hence its relevance becomes time-bound. The ever-dynamic nature of the human is responsible for the big data becoming obsolete quickly. The speed with which this big data is generated is slower than the speed with which it becomes obsolete. This becomes a major problem when this big data is to be used for policymaking and for formulating certain regulations or framework of some kind.
v Reliability of the Data: The very purpose of big data is to identify underlying trends and behavioral patterns especially in relation to humans. The question arises- what if the data collected in phony or is not reliable? The question mark on the fidelity of the data and the quality of the same dilutes the very usefulness of the big data. This question of doubt on the trustworthiness of the big data comes from the amalgamation of many factors. These contributing variables can be well explained with the help of examples.
One of the good sources of capturing big data is social media sites. But the question again arises- How truthfully do people portray themselves on these sites? This becomes a problem when identifying the true behavioral patterns of the users. Another source for the collection of big data is the administrative data i.e; data collected by the organizations of their clients and customers. These may include details of students and staff in a university or a college, details of patients maintained by the hospital, details of customers of a gym or vacation club, etc. The question in the above cases arises- How comfortable are the customers in providing their details to the organizations? The fidelity of the data is again questionable.
v Big data can create Data Deluge and Redundancy: No doubts how big data has really changed the way businesses are dealing with their customers and continue to satisfy their needs. Simultaneously big data has also lead to data deluge which ultimately creates a vague picture with regards to the problem to be solved. Practices like data mining, data analysis, and data manipulation become the solution to the problem of data flooding.
The data becoming redundant also adds to the problem for many organizations as the crux of the underlying trends is lost in the huge volume of data. It thus becomes paramount for us to have a database with us which is reliable, indicating a true trend and pattern rather than a humongous data set possessing minimum quality.