Introduction To Big Data

DEC 03,2022
Duc Anh

The rise of Big Data is undeniable in the evolution of global technology. Read this article to learn more about its application.

Academic studies show that companies that use data and business analytics to make business decisions are more efficient and earn a higher return on equity than competitors that do not. It is consistent with our belief that companies can benefit from opening up internal communication channels, strategically involving customers, and offering communication based on Web3. Big Data will become a valuable asset for businesses in the industry and act as a strong brand, one of the core bases for competition.

1. What is Big Data?

Many definitions of Big Data have been published on information sites and by technology experts. In this article, we will use the description in the Big Data book to explain:

Big Data is a process to provide insights into decision-making. This process uses people and technology to quickly analyze large amounts of data of different types from various sources to create a stream of actionable knowledge. These data are generated via social networking interactions, scientific data, sensors, mobile phones, and their applications, as well as online transactions, emails, audio and video files, photographs, click streams, postings, logs, health records, and other data. They are stored in databases, which grow dramatically over time and become more challenging to collect, arrange, organize, store, administer, disseminate, analyze, and visualize using specific database software tools.

2. Five critical factors in Big Data

Big Data consists of 5 main factors known as "5V.", which include volume, variety, value, veracity, and velocity:


The data foundation is made of a massive amount of information. Big data comes from different sources and is classified into three main categories: Structured, Semi-structured, and Unstructured. Of which, about 95% of the data is unstructured in existence globally. Common examples of unstructured data are user content from social networks (Facebook, Instagram, Twitter, etc.), images, videos, monitoring data, sensor data, call center information calling, geolocation data, weather data, economic data, government data and reports, research, Internet search trends, and web log files.


Data is larger than Terabyte and Petabyte. Data's massive scale and proliferation go beyond traditional archiving and analysis techniques. By definition, volume is the initial size of the data collection, which is the basis of Big Data. If the volume is large enough for an organization, it can be considered Big Data. However, whether there is a particular size of information to be considered "Big Data" or not is still a debatable topic, which is determined by other computing methods.


An organization using big data will have a large and continuous stream of data generated and delivered to its final destination. Data can flow from machines, networks, smartphones, or social media. This data needs to be processed and analyzed quickly and sometimes close to real-time. For example, in the healthcare sector today, many medical devices are manufactured for patient monitoring and data collection. The data collected from medical devices in hospitals to wearables must be sent to their destination and analyzed quickly.


It deals with the quality and accuracy of data. The data collected may need parts, be inaccurate, or provide inaccurate, valuable insights. Authenticity, in general, refers to the level of confidence in the collected data. Data can sometimes become cluttered and unwieldy. Large amounts of data can cause more confusion than insights if the data needs to be completed. For example, in the medical field, if the patient's data on the drug is taking is incomplete, the patient's life can be at risk.


The value of Big Data depends on how organizations can systematically manage and allocate the information. The ability to extract information from Big Data is also very important because the more insights Big Data can collect, the more valuable it is for your company.

3. Application Big Data for Business

Organizations in any industry that own big data can use it to solve real-world problems with careful analysis. The application potential of Big Data is divided into five categories: 

  • Healthcare: clinical decision support systems, personal analytics applied to patient profiles, customized medication, performance-based pricing for employees, illness pattern analysis, and public health improvement.
  • Public sector: establishing openness through accessible, connected data, discovering demands, improving performance, customizing actions for appropriate products and services, decision-making using automated systems to reduce risks, and inventing new products and services.
  • Retail: in-store behavior research, variety, and pricing optimization, product placement design, performance improvement, labor input optimization, distribution and logistics optimization, and web-based marketplaces.
  • Manufacturing: better demand forecasting, supply chain planning, sales support, developed manufacturing processes, and online search-based apps.
  • Personal location data: intelligent routing, geotargeted advertising or emergency response, urban planning, and new business models.

Besides, the Web is also an excellent opportunity for technology investors and businesses. For example, social media analytics, such as understanding user intelligence for more targeted advertising, marketing campaigns and capacity planning, customer behavior and purchasing patterns, and segmentation of emotional accumulation. Following these inferences, companies optimize their content and recommendation engines. Byte Dance's social network Tik Tok is a typical example that has been growing in recent years; they have built AI that collects and analyzes user psychology based on information such as images, audio, video, interactivity, and screen time for quick new content recommendations. TikTok has successfully created an addictive social network for about 81% of users under the age of 35 when applying artificial intelligence and big data and the psychology of each micro-user. 

4. Summary

Amazingly, you can find a way to assimilate giant data collections into systematic segments that everyone within an organization can access. In a dynamic market such as Vietnam, Big data is one of the factors that help businesses create a competitive advantage and become the leader in their industry. At the same time, building big data systems is a significant difficulty for businesses. To understand and get early information about Big Data, subscribe to Melisoft Blog's emails.

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