Big Data is transforming our daily lives and is being utilized for customized services by businesses and governments. However, it also raises privacy concerns, making it crucial to strike a balance between convenience and surveillance.
Vacation Episodes and Big Data
It’s been two weeks since vacation started. I woke up late again today and was surfing the web when my phone suddenly rang at 11:30. It was a discount coupon for boxed lunches from the G Convenience Store near my house, which I frequent. Since I was hungry anyway, I thought it was perfect timing and quickly went out to buy a lunch box. After eating the boxed lunch, I logged into the online K Bookstore to order three books to read during the break. After adding all three to my cart, I noticed a book I’d wanted to read but hadn’t gotten around to appeared in the recommended books section on the right side of the screen. I ended up ordering a total of four books, including this one. Suddenly, a friend messaged me, asking if I wanted to grab drinks near Gangnam Station that night. In the past, I would have declined because the subway stops running at night, but these days, the new late-night buses drop you off near your home, so I readily accepted. Whoever designed it, that one late-night bus route is brilliantly planned.
The situation above is a common everyday occurrence for people these days. But hidden within it is cutting-edge technology that most people aren’t aware of: Big Data.
What is Big Data?
Big Data refers to the vast amounts of data generated in digital environments, characterized by short generation cycles. Big Data can take various forms, including not just numerical data but also text, images, and more. Utilizing Big Data means analyzing the massive amounts of data generated during business operations to create value. Through analysis, more efficient systems are built to increase sales and profit margins, and to predict the future.
What distinguishes big data from the statistical data analysis that existed in the past? While past statistical analysis involved collecting necessary data for analysis, big data encompasses all data generated during business operations itself, not collected for a specific purpose. This results in an enormous difference in data volume. Furthermore, processing speed is a critical issue in big data. For instance, in inventory management, real-time analysis and verification of inventory levels are crucial. For these reasons, utilizing big data was difficult in the past. Disk storage was expensive, so not all generated data was saved, and analyzing data took a long time. However, advancements in the electronics industry have made it possible to store enormous amounts of data at low cost and analyze it in real time.
Big Data’s New Value Creation: From Businesses to Governments
Google, a leader in big data, has been leveraging it effectively for a long time. A famous example is how Google analyzed patterns of people searching for ‘Influenza’ in the US, enabling it to detect the spread of the flu faster than the US Centers for Disease Control and Prevention (CDC). People tend to search online for treatments or medications when they experience flu symptoms or encounter infected individuals nearby. Analyzing the volume and geographic distribution of these searches allows for the identification of areas where the flu is spreading.
Episode’s G-Convenience Store and K-Bookstore customer-tailored marketing is one of the famous examples of big data utilization. It recommends products associated with, or frequently purchased by, customers who bought or browsed similar items. Offering discount coupons for bottled water to customers who frequently buy it at the supermarket, or recommending cheese that pairs well with wine to customers who purchase wine, would increase store sales.
In the fast fashion industry, ZARA collaborated with MIT researchers to develop a system that analyzes sales and inventory data from stores worldwide in real time. As a fast fashion brand, ZARA prioritizes real-time trends and customer demand. Inventory was their biggest challenge. They adopted big data for efficient inventory management, achieving successful results.
Big data isn’t limited to numerical analysis. It can analyze text, images, and even video. Google Translate, provided by Google, translates by recognizing patterns based on existing massive translation documents. This method translates better than computers recognizing words for translation. Korean-English translation is still imperfect, but translation works well between European languages with similar word order, as there is a large accumulation of existing translation data.
Big data is primarily used by companies, but there is also a growing movement for governments to utilize it. Last year, Seoul City analyzed 3 billion call volume statistics obtained from KT, covering the period from midnight to 5 a.m. This analysis identified areas with high nighttime activity, which were then used to establish new late-night bus routes. This case gained popularity as a big data application in the public sector. The Financial Supervisory Service announced plans to build a ‘Credit Monitoring System’ using big data to preemptively block illegal loans by savings banks.
The Rise of Big Brother?
Big data technology isn’t without its drawbacks. Concerns are emerging that big data could usher in the era of Big Brother. Big Brother, featured in George Orwell’s dystopian novel, represents an authoritarian power that monitors and controls society by monopolizing information.
Particularly, the risks associated with corporations’ collection of personal information and excessive surveillance are being highlighted. For several years, opinions have consistently been raised questioning whether companies primarily dealing with big data, such as Google and Facebook, are collecting and monitoring personal information excessively. Credit card companies and the retail industry, which engage in customer-tailored marketing, are also facing criticism for excessive invasion of privacy. Furthermore, personal information leaks have frequently occurred in the financial sector recently, raising doubts about whether it is safe for companies to collect and store personal information for big data analysis. This is because if such information leaks due to lax corporate security systems, it could cause serious societal problems. To solve this issue, laws and systems governing personal information use, well-reflecting public opinion, must first be properly established. Furthermore, companies should refrain from collecting unnecessarily excessive information and must focus more on information security. Whether big data becomes a force for good or evil depends on the government, society, businesses, and us.
