Data mining & pattern recognition are important subfields in the domain of computer science. It deals with the collection, integration & analysis of large data sets, with the purpose of discovering underlying patterns or insights useful for taking business decisions & predictions. Pattern recognition is an important part of this process where the hidden, underlying patterns are identified by using machine learning algorithms. Statistical information extracted from patterns and/or their representations is then converted into actionable insights used in giving competitive advantages to the clients. R is the most popular programming language used in statistical analyses, so both data mining & pattern recognition can be performed skilfully in R.
Data mining is an absolutely necessary skill for data scientists & analysts. Whenever dealing with large amounts of data, one has to sift through & gather only relevant data & try to automate the process as much as possible. This is possible through various mining methodologies in data mining.
Taking business decisions & converting them into actionable insights is not possible without learning to recognize the underlying data trends & patterns; this skill can be acquired through studying pattern recognition. Various tools for pattern recognition like Matlab, Python, etc are freely available which, when used with expertise, are very much effective.
Data mining & pattern recognition is not only for data scientists. People seeking employment in different domains like business development, database management & administration or data processing should also possess the necessary skills required to mine data, process them properly to recognize the hidden patterns in them so that proper actionable insight can be taken. Hence, this is an essential skill to have.