Written by Student Reporter (Erwin Josua - EMBA, 2021)

Right now, we’re living in a digital world phenomenon. It’s common for most people to live on the Internet of Things. Out of approximately 7 billion people estimated worldwide, about 5.2 billion are mobile users, 4.66 billion are Internet users, and 9 out of 10 are active Internet users worldwide. With so many digital media users around the world, the data produced has developed enormously.

This is also followed by an increase in social media, which is becoming more and more prominent. In addition to the rise in demand, it tends to grow. With so many digital media users around the world, the data generated has increased exponentially. At a virtual meeting held by ITB’s Decision Making and Strategic Negotiation Lab in the DMSN Talks Series 2020 (17/12/2020), the CEO of Technaut Education, Muhammad Apriandito Arya Saputra said that at the end of 2020 there were 40 million zeta bytes of data generated and they still continue to grow. “This is what many people say as big data. Currently, many parties are now considering the potential for the use of this massive data for various things,” he said.

As a data scientist, he also discussed the importance and features of big data. “Basically, big data is a term about data with very large and unstructured volume,” he said. The characteristics that can be defined from big data are as follows:

  1. Volume. The huge and abundant amount of data is essential to the character of big data. Where the measured data is not only in a thousand but maybe a number of data with many more zeros.
  2. Variety. Diverse and not just one form of data. The variety of data generated can be in the form of text, images, videos, sound, and various other types of data.
  3. Velocity. Apart from the number and variety, very rapid growth is one of the characteristics of big data. The data produced can be easily generated through cellphones, computers, sensors, and other data generators.
  4. Veracity. If we look at the consistency of the data produced, we can conclude that there are still limitations. This is focused on the use of computers that have different human decisions when recording data.

Data Mining and Data Analytics

Big data has a lot of potential as raw data that can create new insights as well as great ideas. We can extract data that represents the digital footprint of Internet users in the form of user behavior predictions. Where the study of consumer behavior can be used here to find solutions to the problems and to find the added value of the product.

From the data that has been processed, the findings that come from social media analytics can be diverse kinds that are customized according to the needs. We may look for forecasts of people’s activities at certain times, food preferences, desires, geographic public discussions, perceptions, attitudes, patterns, trends, competitive markets, and so on. “For example, on Valentine’s Day, many of Facebook’s personal statuses became complicated. Since discussing it more closely, this may have been attributed to someone who neglected to celebrate this day of love with his partner. This perspective may constitute an inspiration and a role for psychologists to empower people who have issues in their relationships,” said the man who is in the management of the Indonesian Data Scientists Association.

“We also found the trend of haircuts during the pandemic which was analyzed through social media Twitter. These days, many people choose to cut their hair in a different style than usual or cut their hair themselves for a new spirit. But unfortunately, social media analytics show a trend of disappointment with the new haircut, ” he continued. In addition, there are still a lot of possible new insights from the use of social media analytics. Let us hope that these new examples of insight will make us aware of the use of big data. As well as providing us with a new awareness that this digital phenomenon is being encountered together.

Additional reference

Data Reportal. (2020): Digital Around The World.