Why Big Data Needs Thick Data?

Introduction

The debate on Big Data and why Thick Data must be incorporated with it, has been going on for a long time. It has been noticed that Big Data is just not working along with the organizations anymore. While it can be seen that the Big Data industry has been growing and it has exceeded the mark of 122$ Billion, however; in the year 2017, about 60% of the projects failed.

Out of the total organizations in the world, the efforts of about 45% of the organizations are on the verge of breaking and 12% are saying that it is quite soon to give any judgment. About 11% of these organizations are bankrupted and only 27% of the industries are bearing fruitful results but for how long?

Why Big Data Is Not Working?

Several reasons may have caused the downfall of Big Data such as the usage of ineffective techniques and tools or incompetent leadership. However, the most noticeable reason is the deep involvement in the figures or numbers rather than showing any interest in the qualitative nature of the products. Sure, the numbers are important but marginalizing and suppressing the elements of human emotions can lead the path to failure.

Big data referred to as the quantitative information collected by the interaction between the organization and the customers. This information contains all the information that can provide insights for analysis and to draw out specific patterns for better decision-making. For example, if we look at the Airlines, the quantitative analysis has enabled us to improve efficiency by increasing their capacity and services they perform on routes. However, if we want to look at the behavior of the customers and what is demanded in the market, we need more than just quantitative information.

Thick Data VS Big Data

As already mentioned, Big Data is the quantitative information while the Thick Data is the data extracted by using ethnographic methods and revealing the true emotions of the people regarding the products. In other words, Thick Data is referred to as the qualitative information unleased by exploring the mindset and stories from all around the world.

While Big Data counts on the Machine Learning for deploying, processing, and analyzing the given set of data, Thick Data works on human learning to unveil the social context hidden in the data. Big Data requires a large amount of data to interpret information from the hidden patterns in the information, Thick Data only requires a small amount of quantitative information to visualize the human patterns.

However, it must be kept in mind that all the organizations make use of both the data to ensure the prosperity and economic stability of businesses. Both of these are essential to provide different depths and scales to acquiring the required information regarding the products and the customers.

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Merging of Big Data and Thick Data

Big Data produces an abundance of information that needs a helping hand to connect all the dots and fill in the vacant gaps. Thick Data acts as this helping hand and fill in all the gaps as it is best to map out all the territories which would be otherwise to map and makes sense. The provision of qualitative data inspires organizations to gather insights and come up with innovative ideas for the betterment of the businesses.

Sometimes, Thick Data doesn't provide what we expect but it can definitely bring us the information to help in effective decision-making. The merging of Big Data with Thick Data can help you make improved ties with the shareholders as it gives you all the depths and scales required for the efficient deliverance.

Where Big Data incorporates figures into the systems, the Thick Data incorporates into the hearts of the people for better understanding, developing trust, and creating an atmosphere of transparency to tie all knots. Decision-making depends upon the rationality of the organizations but it also depends upon the emotional connectivity between the brand and the stockholders.

Opportunities Followed by the Merging

Usage of Big Data alone can create problems but the collaborating Thick Data with it can open a stream of opportunities for you. The following are some of the organizations where this collaboration has driven fruitful and profitable outcomes.

• The sector of Health Care utilizes both Data and procreate projects like Asthma Files which can be referred to as a start to a revolutionary phase to solve the health crises globally.
• Social Media Analysis incorporates the merging of Big Data and Thick Data to provide efficient influencers and to look out for the latest trends.
• Service/Product Design implements Big Data for critically analyzing the raw data whereas Thick Data provides the insights of what people actually want.
• Mobile Companies need Big Data to make the personal information of the customers anonymous whereas Thick Data is incorporated for revealing the social and personal context of the data.
• Brand Strategy consumes both Big and Thick Data to analyze the information and to understand the desires of the consumers.

End Points

Thick Data may counterbalance the effect of Big Data but it cannot suppress the demand and effectiveness of Big Data. Just as Thick Data is essential for the Big Data but Thick Data is also dependent upon the Big Data.

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