Understanding the revenue deficit or high turnover in the business was difficult a few years ago. To find the root cause then, employers had to dive deeper into the problem and the results were totally subjective. Thus, there was a higher probability of the results being wrong and conjectural. However, the onset of Big Data has resorted the problem and facilitated employers, as well as other professionals, in discerning the issue. Hence, data is imperative for decision-making and advancement related subjects.
Reliability on Big data has primarily surged after witnessing the market boost, through the implication of the data. Despite the job creation and serving precise data, the realm of Big data has not come up with resolutions yet. The data has not rendered solutions to various problems such as encouraging the employees, resorting to cost-effective ideas and begetting cohesion amid team players.
Men Grow Anxious To Learn Big Data
Since the beginning, learned minds are anxious to know what data is. Students amid the lot, are most concerned to understand conglomeration of data and business. Both the segments are diverse but are also connected by a cord. Employment generation, easing the decision-making process and analyzing the behavioural patterns are yielding benefits of the data.
Till now, the data has answered the root cause of the problems but it has failed to tell what one should do to fix it. It helps to anticipate changes in the offing but it can’t answer how to halt the unfavourable changes.
Take a realistic example of a business leader, who desires to utilize data to improve analytics and regulate risk factors. After implying the data, the employer receives a research report but he does not receive the solution to resolve the issue. So, the data can only answer “how”; it cannot answer “why” which is the crucial part to be talked about openly. Similar to this example, there are multiple companies which have utilized data to make sound decisions.
In 2016, CNBC reported that the famous coffee shop, Starbucks utilized the data to ascertain the consumers’ preferences. The brand garnered data to understand the market and accordingly, launch their store products. Big Data was on the rise during that time and coffee shop witnessed the surge and implicitly employed it.
“Using consumer data, the coffee chain designed its new line of products to complement the habits it gleaned from its own stores. Basically, the company says it talked to its baristas about how customers ordered coffee, lattes and tea while in Starbucks locations and culled several industry reports about at-home consumption. It used that data to create K-Cups and bottled beverages to sell in grocery stores.” reported by CNBC.
The research conducted by the company was not intricate, thus, the resolution was almost in front and easier to perceive. In the opposed situations, resolutions can’t be conceptualized effortlessly.
Inability To Correctly Apprehend Individualistic Study
Individualistic behaviours which change suddenly, can’t be understood by Big data. Thus, the process of solving the individual’s issues can’t be accessed through data. These drawbacks don’t weaken the idea of using Big Data; they mainly question the dependence upon it.
Human traits are diverse and significant in their own manner. Research and data can’t describe human instincts and behavioural patterns in a book form. For understanding the employee’s turnover rate or failure in the business, it is imperative to rip out the issues from the foundation and avert the business from getting stagnant.