Big data is playing an integral role in the strategic planning of businesses and governments through the analysis of large amounts of information, enabling innovation across society. The era of efficient data utilization has come to determine competitiveness.
Big Data is the latest buzzword in the IT industry. At its simplest, big data literally means large amounts of information. In the past, large amounts of data were difficult to manage and utilize, so they were either stored or utilized by only a few companies or organizations. However, with recent technological advancements, big data has become an essential concept in almost every field.
Big data is a large collection of structured or unstructured data that exceeds the capabilities of traditional database management tools to collect, store, manage, and analyze data. Structured data refers to structured data such as numbers, while unstructured data includes unstructured data such as text, images, and video. As data becomes more diverse and complex, the processing of big data presents complex technical challenges that go beyond simple data management. Although it contains as much information as it does, unrefined information is nothing more than a useless jumble that just takes up memory capacity. Therefore, the meaning of the term big data has come to encompass more than just the large amount of information itself, but also the techniques for analyzing it and deriving meaningful results.
The rapid decline in storage costs due to advances in data storage technology has made the creation of big data possible, and the amount of accumulated data continues to grow exponentially. For example, the amount of information accumulated in the five million years since our direct ancestors, Homo sapiens sapiens, appeared on Earth has doubled in the last year and a half alone, a fact that underscores the explosion of large volumes of data. This exponentially growing amount of information is deeply embedded in the lives of businesses and individuals, and has led to an era where data is considered an asset. Even now, our information is constantly being transmitted and recorded through devices like smartphones, building yet another database.
The current trends around big data are even changing the hegemony of market competition. Until recently, what mattered most in the marketplace was information power – who had what information was the measure of competitiveness. But with so much data being drowned in the flood of data that never sees the light of day, it’s what you do with it that matters. When it comes to data analytics, it’s not just about accuracy, but also about analyzing massive volumes of big data efficiently – in real time – to derive real-time strategies. This is why ‘big data analytics’, a methodology for analyzing and utilizing big data, is gaining traction, as even the most accurate analysis is useless if it cannot keep up with the speed of changing trends. It’s not just about analyzing data, it’s about extracting insights from vast amounts of data and utilizing them in real time.
Big Data Analytics is the field of these techniques. Big data analytics, which analyzes data in real time at a volume that exceeds our imagination, is like mining for sparkling gems in a dark mine of data, which is why it is also known as data mining. Data mining is the art of finding meaningful patterns in big data, and it plays an essential role in helping companies gain a competitive edge in a sea of information.
A common use case for data mining is in product marketing. In marketing, it’s crucial to quickly gather consumer feedback to inform product strategy. If you have sales information about who, what, and when they buy, it will be easier to target key customers and market to them effectively. The most important conduit for retailers like hypermarkets to get this information is loyalty cards. Most of us have been asked, “Do you have a loyalty card?” when making a purchase at the grocery store. If we don’t have a loyalty card with us, we’re asked to enter our phone number, which shows how flexible this system is in collecting customer information.
Companies’ loyalty strategies are designed to make a data link between our personal information on the loyalty card and the products we buy. In other words, in exchange for rewarding customers with points, retailers get data on who buys what, when, and how much. This data is critical for marketing products. Until recently, however, manufacturers had no access to this customer information, as they only supplied products to retailers such as big box stores. This made it difficult for manufacturers to get good material for marketing.
However, a distributor who already knows a lot about their customers would make the following offer to a manufacturer “We’ll give you the customer information we have!” ‘We’ll make a marketing strategy for your product with the information we have!’ By making such offers, distributors have gained an advantage in dealing with manufacturers. Therefore, distributors have earned a lot of money not only through the distribution process but also through customer information. As you can see from these examples, until recently, companies with information had hegemony in market competition.
But recently, with the rise of social media and blogs, manufacturers have begun to fight back. This is because even if a manufacturer can’t see the customer directly, they can still hear the customer’s voice about their product through the open source of information that is the internet. This has shifted the competition between companies from just having information to being able to use it well.
A prime example of this reversal is the ready-to-eat food product Hatban. While retailers, including hypermarkets, had information about the customers who were buying Hatban, there was one thing they didn’t know. They didn’t know why customers were buying and consuming them. CJ, a South Korean company that manufactures the product, collected posts about the product on social media and analyzed them using a data mining technique that deals with unstructured text data. Before the analysis, many people predicted that the consumption of the product was mainly outside of the home, such as when traveling. However, the manufacturer’s analysis showed that the consumption of the product was mainly for mothers to serve to their families when there was no home-cooked meal available. The data mining didn’t stop there: a sentiment analysis of the words in the text also revealed that a mother’s emotion when making a meal for her family with a hatban is one of remorse. The manufacturer’s advertising and marketing efforts were guided by these findings, which are reflected in the copy of a recent hatban ad. “Don’t feel sorry for the meal your mom cooked for you!” The ad, which reflected the results of this trend analysis, resulted in a significant increase in product revenue.
Manufacturers who have made good use of the myriad of information available on the Internet through data mining techniques have been able to successfully market without dealing with distributors. In this way, the hegemony between companies in market competition is changing depending on who is good at data mining techniques to unearth gems from a given mine of data.
The utilization of big data is no longer limited to specific companies; the public sector is also using big data to formulate various policies and improve services. Governments are actively leveraging big data to find solutions to social problems and provide personalized services to citizens based on large-scale data. This data-driven approach is enabling more efficient and transparent administration and contributing to a better quality of life for citizens. Big data is also transforming healthcare. Collecting and analyzing individual health data is enabling personalized treatment and prevention, predicting the spread of infectious diseases and enabling rapid response.
In the end, despite its sheer volume and complexity, big data can be a powerful tool that, if handled correctly, can drive innovation across our society. With this flood of information constantly being generated, businesses, governments, and even individuals will need to recognize the importance of big data and figure out how to use it effectively.
To keep up with these changes, continued research and technology development in big data is essential. Along with the advancement of big data analytics techniques, the ethical use of data is also becoming increasingly important. The protection of personal privacy and the transparent utilization of data are issues that we must address in the era of big data, and solving them will require not only technological advances but also legal and social discussions.
In conclusion, big data has been called the new oil of the 21st century, and its value depends not only on the amount of data itself, but also on how effectively it is utilized. The ability to handle data is now becoming a critical factor in determining the competitiveness of companies and countries. Recognizing the importance of big data and having a strategy in place for how to leverage it will prepare you for the future.
