Dear Deeman,
There is a nice answer given by Mr. Sanjay Chakraborty. Data mining is basically a broad term which indicates the process including AI, statistics, or any other techniques. In short, it is a hybrid process. On the other hand, Statistics is an elementary approach.
Data mining consists of two terms;data and mining. Data term refers how we can collect and pre-process that data according to our purpose. Whereas mining require one analysis process which is called statistic. Data Mining is presented as a Specialized discipline: "Applying statistics and pattern recognition to discover knowledge from data". Then when you use data mining in base of sound mathematical methods by mean of heuristic software and you study the facts you are doing Statistics. Statistical analysis is designed to deal with structured data in order to solve structured problems. Data mining is designed to deal with structured data in order to solve unstructured business problems. Sometime, data mining is designed to deal with unstructured data in order to solve unstructured problems(such as, text mining).
Statistics is the academic subject concerned with reasoning about statistical quantities, such as comparing the means of two groups or exploring the relationship between two variables. It usually starts with a specific objective.
Data mining is the process of looking for unexpected patterns in a data set.
Dear Deeman,
There is a nice answer given by Mr. Sanjay Chakraborty. Data mining is basically a broad term which indicates the process including AI, statistics, or any other techniques. In short, it is a hybrid process. On the other hand, Statistics is an elementary approach.
Data mining is extracting data from large database(Warehouse). Statistics means analyzing data and we created a report.
Data Mining is part of Statistics. Perhaps the contest you have in mind rather is between Data Science versus Statistical Inference. In my opinion the difference is well explained in the new book by Efron and Hastie "Computer Age Statistical Inference": the former (data science) is more about what you (can) do ( powerful algorithms made viable by computer-age processing capabilities), the latter (statistical inference) is more about why you do it (its inferential justification or accuracy assessment).
Deeman,
This is a good question but cannot be answered in a few words. Data mining uses machine learning algorithms to mine large data, so they are less restrict to assumptions. Data mining does use some statistic-based methods such as regression, factor analysis, or cluster analysis. But it also includes many rule-based methods such as decision trees, random forest, gradient boosting, etc.
I have taught data mining for 8 years and uploaded my lectures and video tutorials on my Youtube channel. You can visit my channel here https://m.youtube.com/channel/UC5FyLi7i6vY7bhcgzpq7oTA. Let me know if you have any question.
DT
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