BIG DATA FOR IMPROVING CUSTOMERS’ EXPERIENCE

The concept of big data is a discussed topic nowadays. Companies are looking for opportunities on how to gather, analyze and benefit from this information. We would like to provide several words about roots and history of big data because it will help us to understand better this phenomenon.

BIG DATA HISTORY
You might be surprised but the roots of big data go far away in history. The importance of information was understood in ancient civilizations of China and Rome. Of course that was not digital data but the idea of collecting and analysis appeared at that time. Digital data emerged in 1950’s – 1970’s when first computers opened the door to our every day life, technologies became capable of digital data storage. The real revolution in technologies and big data as its part was introduced by the Internet. The usage of the Internet dramatically increased data production. Three wales on the digital market were first to develop technologies for handling large-scale web data, namely Google, Amazon and Yahoo. The definition of big data was introduced in 2001 by Dough Laney. He defined big data with 3Vs frame work – volume, velocity variety.

BIG DATA: 3Vs FRAMEWORK
Volume (or amount of data) refers to size of data being generated, stored and processed; deals with terabytes, petabytes, and sometimes even exabytes of data (far beyond databases’ capacity). Huge data volumes make it possible to gather information from various sources such as social media, transactions, IoT devices, etc. For instance, Facebook processes over 4 petabytes of data daily from posts, images, and videos. Google handles over 8.5 billion searches per day, generating massive query logs. IoT devices (smart meters, cars, wearable tech) continuously generate vast amounts of real-time data.

Velocity (or data processing speed) concept refers to how fast data is generated, collected, and processed in real time. In modern applications, data needs to be processed immediately or within milliseconds. It is significant because businesses require real-time insights to make decisions quickly. Delayed processing can lead to missed opportunities or security risks (e.g., fraud detection). For example, Stock Market Trading: Algorithms analyze millions of stock transactions per second to predict trends. Credit Card Fraud Detection: Banks detect fraudulent transactions instantly before approval. Social Media Trends: Twitter analyzes tweets in real time to detect breaking news or viral content.

Variety(or different types of data) refers to variety of data formats (structured, semi-structures, unstructured) from different sources. Traditional databases are capable to store only structured data (columns, rows, tables) and big data on the contrary includes more complex data formats. Here are some samples for you, Netflix & YouTube analyze user watch history (structured), comments (semi-structured), and video content (unstructured) to recommend content. Google Maps combines traffic reports, GPS signals, and weather data for navigation. Medical Industry analyzes X-rays, patient records, and doctor notes together for diagnosis.

Over years experts expended the concept and added three more Vs to make the definition of big data deeper and more specific – veracity (accuracy and reliability of data), value (useful insight for businesses), variability(context changes).

BIG DATA FOR IMPROVING CUSTOMERS’ EXPERIENCE
Information is a very powerful tool and business owners are aware of that. Here are the most effective options how big data is used by businesses.

CONCLUSION
The term big data is relatively new, but the idea of information analysis goes back to ancient civilizations. The more businesses know about their customers and their behavior the better solutions they can introduce and increase their revenue. The emergence of the Internet made a revolution in terms of data, users began to produce enormous amount of unstructured information. It became much easier to follow their behavior patterns and tastes when relative tools are available. Big data is a significant asset that can and should be used by businesses.