Datafication: Applications and Implications

“Wal-Mart is able to take data from your past buying patterns, their internal stock information, your mobile phone location data, social media as well as external weather information and analyze all of this in seconds so it can send you a voucher for a BBQ cleaner to your phone - but only if you own a barbeque, the weather is nice and you currently are within a 3 miles radius of a Wal-Mart store that has the BBQ cleaner in stock.” - Bernard Marr

Everything that was previously invisible can be quantified and measured today, thanks to Datafication. Datafication is a process of transforming a process or activity into data that can be tracked, monitored and analyzed, leading to new opportunities in business intelligence, making it a key contributor to the Big Data revolution.

In a person’s daily life, there are many examples of datafication that can be seen. For instance, exercise activities are tracked by wearable fitness devices, tracking calories burnt, time and intensity of workout. They also suggest new routines and nutrition based on one’s workout history.

The GPS application in one’s phone suggests an optimal route based on data such as location, traffic and weather conditions. As one browses the internet, behavior, such as the number of clicks, the web pages visited and time spent on a page are analyzed to improve user experience of websites.

Social networking websites generate humongous data. A person’s thoughts, through tweets and status updates on social networks, are being datafied. Sentiment analysis, social network analysis, etc. are being performed on this data to understand public emotions, identify communities of closely-connected people and derive statistics on social causes and health issues. Other websites such as LinkedIn, Foursquare and Spotify are tracking and quantifying professional connections, location and music preferences respectively and using it in predictive analysis.

This data is often used for targeted advertisements and marketing by organizations. Consumers are not aware of the legal contracts they are agreeing to simply by using mobile applications and social networks. While targeted advertisements are useful, the consumer does not have complete control and awareness over the permissions being given by him. The recent Facebook social experiment where users’ news feeds were manipulated created an uproar among users because they believed that the experiment invaded their privacy. However, Facebook stated that signing up for Facebook itself gives Facebook the authority to use data for their own purposes. In other words, there was a clear misconception among users about the permissions they had given Facebook.

This kind of business intelligence is useful in many ways, but at the same time has privacy and security implications. Users must have more control over their own data. Further, Government and other regulatory bodies must come up with a standard framework for protecting data from misuse.

It is our team’s belief that while datafication is key to 'Big Data' revolution, there are legal ‘grey areas’ that need to be addressed by the regulatory bodies.

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