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What is Datafication in data science

What exactly is Datafication and how is it created?

Before we begin, let’s know the definition of data. Information that can be converted into a format that is effective for processing or moving around is referred to as data in computing. It is currently in binary digital form.

Data can be created in many ways by someone who uses technological devices. This includes email, credit card payments, unlocking personal devices, monitoring social media, and shopping online. Children generate data when playing games, browsing social media, and shopping. Bosses generate data as they wander through sensor-equipped smart offices or when their car registration activates automatic garage doors. Phones also broadcast data, updating location, adding it to images, and, if permission is granted, letting other devices know precisely where they are.

Sensors gather information from multiple sources, such as the sun, rain, smart home devices, and security cameras. This information is linked to consumer profiles, store data, and ATM security cameras.

The datafication process in data science

  • The phrase “datafication” describes the process of converting digital interactions into records which can be collected, analyzed, and ultimately sold. It gained popularity due to the early definitions of “big data” provided by Mayer-Schoenberger and Cukier (2013).
  • Understand that to facilitate real-time tracking and predictive analysis, data collection is a continuous activity that entails transferring as many parts of our lives as feasible into computerized data. Due to continuity concerns, information is routinely acquired, processed, and stored on specialized data infrastructure, the majority of which is held by governments or businesses.

Why is this shift occurring?

  • This shift is mostly because routines and habits that are transformed into data may be tracked, evaluated, enhanced, and made profitable. This gives companies the chance to turn human behaviour into useful information that may change fundamental corporate strategies and impact consumer behaviour. or for social agencies to promptly find those who want assistance. Data is generally more valuable the more valuable it can produce.
  • Although businesses are not currently employing data, they may still gather and store a large amount of data, to use it later. Consequently, companies can now start gathering information on previously untraceable procedures. Additionally, after processing, they can become data-driven, which lowers the risk of releasing new goods or services onto the market.


The industrial period brought about a transformation in our lives, with computers and accessible internet connection changing how we live. Corporations and governments gain from ongoing surveillance as the number of devices producing data grows. However, the idea of datafication raises concerns regarding individual user fairness, control over dataset access, identifying breaches, and extending the “right to be forgotten” to many devices collecting dark data.

Properly managed datasets, governed by law, security measures, and work ethics, may result in less aggressive advertisements and more customer-friendly services. Simply gathering thousands of records, might enhance each experience by excluding brand size and name as decision factors in choosing a supplier.

It is critical to verify databases for data types, volumes, and security levels to avoid falling behind. It is critical to ensure that everything is connected, used, and correctly stored to prevent being left alone in the datafication era.