Data Mining and Inference Techniques

What is Data Mining?
Data mining is the process of discovering certain patterns in large data sets that involve methods at the intersection of machine learning, statics, and database systems. It is an essential process where intelligent methods are applied to extract data patterns.

What are Inference Techniques?
Inference Techniques is the process of deriving logical conclusions from premises known or assumed to be true. It is the act of reasoning from factual knowledge or evidence. Basically clues taken from data mining compiled and then use that information to promote a product, or to spread propaganda through the use of social media.

How is it used?
Data mining is used to take big data sets and compile them and look for certain patterns within the data. It could be medical records or it could be social media profiles. So it will scan through each profile and then catch similarities in them, and let you know what are the treads on all the data scanned. It could be that the data scanned showed people at the age of 65 and older have a higher risk of falling and causing serious injury, this is just an example. One pretty famous data mine piece of information is the phrase "drain the swamp". Strategist and data analysts saw that this saying was proving outrage in the community and then continued to push the saying on social media when you hear that term who do you think of exactly. It is also a form of marketing, but the term stuck because the data showed it had a positive impact.

Who uses Data Mining?
All major corporations use data mining since it is such a versatile tool. It can be used for fraud detection, direct marketing, market segmentation, and trend analysis. Not to mention many more, these are the more current uses for the technique. Data mining automates the process of finding predictive information in a large database. For instance, data mining and algorithms can cause user privacy issues due to the fact that user information is gathered to make predictions about what types of things users prefer, which can lead to a search bubble phenomenon if users aren't careful.

Questions that traditionally required extensive hands-on analysis can now be directly answered from the data. "Blue Cross and Blue Shield state organizations, large HMOs, U.S. corporations, state governments, etc. Merck-Medco is mining its one terabyte data warehouse to uncover hidden links between illnesses and known drug treatments"[1].