By Paul Matthews
In 2018, the world has been shaken by the usage of big data: the Cambridge Analytica scandal, which was related to the allegedly illegal buying and selling process of data points and data-related pieces from the British company, has put data science into the spotlight of the “mainstream business” world. After this scandal, in fact, data has surpassed oil as the most valuable asset on Earth. Let’s analyse why and, most importantly, how this has happened.
Data Points: A Commercially Powerful Numerical Value
For “data point”, we intend a numerical value which, when associated with a specific entity (i.e. a person, a company), combines preferences, comments and tastes (from a numerical perspective) in order for a software to automatically elaborate them. The power of data points stands in the fact that, when properly analysed, they could give thorough insights on a particular user’s preference on a specific topic. The “exploitation” of Facebook searches on the Brexit topic, for example, was elaborated using data points to provide highly tailored ads to the people who were either searching for “leave the UK” and related keywords. Although this may sound slightly political, it was actually confirmed by Cambridge Analytica itself last year after they (and Facebook) were fined for over $2 billion for buying and selling private pieces of information (data points).
Data Science: An Enterprise Niche Sector Going Mainstream
The possibility of creating tailored ads based on numerical values has intrigued business owners worldwide to the point in which they decided to open data science-related divisions in companies which weren’t exactly at an “enterprise” level. Data elaboration, acquisition, science and Python development professional figures have been recruited in small and medium companies worldwide massively, in the past 7 months. Despite a specific GDPR section strictly regulating data acquisition and processing, data scientists have definitely “gone mainstream” in the recent past.
From fintech to eCommerce, to pure lead generation, the usage of data science has become a constant in 2019.
Some Business Sectors Have Been Getting More Results Than Others…
As mentioned above, data processing and science have been used by a variety of businesses in the past months. Fintech and real estate have been the most successful ones, in terms of lead generation tailored onto data. Sectors like bridging loans, development finance and similar have seen a net 35% increase in organic investment in terms of hiring Python developers who were able to process such delicate data to prepare targeted, tailored and highly convertible ads for social media channels. Lead generation has become very dependant on data in the recent past.
The usage of data in 2019 has definitely become a mainstream procedure. In the nearest future, we can safely say that GDPR rules will become even more strict: with more specific regulations on the acquisition and storing, data is still far away from being fully regulated.
By Paul Matthews
Paul Matthews is a Manchester-based business and tech writer who writes in order to better inform business owners on how to run a successful business. You can usually find him at the local library or browsing Forbes’ latest pieces. Paul is currently consulting a bridging loans company in Manchester.