Math Series Part III: Data Mining
Digging for Gold: Data Mining
Mathematics is truly everywhere, and there is no exception when it comes to applying it in the analysis and extraction of data. Indeed, the application of statistical techniques and methods of manipulation in order to ‘mine’ the data and information of people from every corner of the world are some of the most prized possessions of big companies the likes of Facebook, Pfizer, and Google. In fact, much of the revenue that billion-dollar companies make today are off the back of huge amalgamations of consumer and user data. This information, which may or may not be anonymous, is sold or used for research purposes or even used to more directly and personally target individual consumers through what has been analyzed to be their personal preferences through data mining. So, what does ‘data mining’ actually mean?
In general, it involves analyzing data from different perspectives and finding patterns between the multiple data sets that are available. For instance, if there is a record through tax returns of how much of their monthly income a family spends on food and of how many visits they have made to doctors over a relevant period through their hospital records, data mining might enable us to find a correlation between the amount of food that the family consumes and how sick they are getting. This example is something a government agency may be interested in as obesity concerns rise in many countries. However, other for-profit companies, such as McDonalds, may be using this data to analyze a huge set of data about how many Big Macs they sell over McChickens. This statistical analysis will guide them in their profit-maximizing decisions and marketing strategies for the future.
Typically, this form of data mining would be done automatically by high-powered computers with advanced databases and artificial intelligence software that is programmed to be able to identify and correlate precise information from billions of purchases and actions and people. This is then turned into human-readable information, summarizing and outlining the key relationships observed, and is passed on to those in charge to be made use of in business decisions.
Even though the process of data mining has existed for years in large retail and consumer service chains, especially where point of sale terminals could track information electronically, there has been a huge increase in nominal businesses’ capacities to make use of data mining through increased online purchasing and unceasing advances in computer technologies and statistical software.
Although the case of data mining is a more applicable tool in everyday life and is a more recognizable and realistic example of mathematics, all of the concepts discussed in this series are tied together by just how remarkable some mathematical models can be in transforming the world we live in and in continuously upgrading how we view and analyze it.