Data Mining: You’re Revealing More Than You Think
The word data is used in every field these days. Most of the companies are presenting their big data, data analytics, data privacy, data warehouse, data lake and much more related information. At the center of data mania, there is data mining which is shifting of all those bundles of information for insights. Data mining is used by various popular companies like Amazon, Google and Facebook to know what a person would prefer to buy or see with accurate estimation. It

What makes data mining more interesting?
Data mining allows airlines to efficiently predict who is going to miss a flight, amazingly it assists doctors to spot fatal infections, and it has even enabled cell phone companies to predict massacres in the Congo. The power of data mining and its hype is making it sound like a magic wand that can sink a business or raise its value to huge numbers.
How does data mining work to give helpful outcomes?
For the record, data mining doesn’t involve any phoenix tail feathers. It is just applied statistics, searching and decoding a lot of data points for patterns. These patterns are not based on human intuitions but on what the recorded data suggests. The information can be subtle or even alien.
For example, the company like Spotify would love to predict what each person would want to listen to. The key to data mining is that it achieves description and prediction not through careful studies by experts but by analyzing large amounts of data. In the case of Spotify, it might include scanning of patterns in genre levels, acoustic attributes, internet reviews, plus the age, location, and other information about each user. It is all about spotting patterns than explaining them.
In classified data, an instance is broken down into a collection of numeric attributes, or features. The system tries to tease out patterns with the help of an algorithm. Many mathematical procedures are followed by computer programs to devise this work. The selection of the best algorithm depends on how different features are connected.
What are the basic features of data mining that contributes to its successful approach?
Regression is to predict a number instead of predicting a particular category. Therefore, it is considered as a predictive policing software. It depends on thousands of variables. It works efficiently by finding an equation to fit the data points and then combines the positive and negative contributions of information to get an estimate. The well-known example of regression is Google Flu Trends which started in 2008.
Clustering is another data mining technique where the objective is to data positions in a way to assist in appropriate analysis. The companies use clustering to group the products. eBay uses hierarchical clustering as its magnificent tool. It emerged in the 1980s and helped millions of companies till then to find strong roots of establishment as well as growth.
How you are revealing more than you think?
Social media has created a boom in the field of data mining as digging data has become a lot easier. Facebook, Instagram, Google, Apple, Amazon, and many other companies have stored information which makes them answerable to the privacy of each individual. The person is tracked and its daily actions are recorded as a database. Choices and preferences are analyzed and the best of advertisement is proposed in front of the respective individual.
Data Mining is an amazingly powerful tool that must be used correctly and properly to make this world a better place to live. It is an incredible mathematical tool which helps in extracting knowledge from data and significantly helps in extracting the useful results.
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