数据分析和数据挖掘的区别

 

Data analysis -- is a process of inspecting,cleaning, transforming data.The goal is to highlight useful information,suggesting conclusions, and supporting decision making.

Data Mining -- Intersection of artificial intelligence, machine learning, statistics 

The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use.

 

Business analytics is a term that refers to the various modes of using information to make business decisions. Traditionally we used to call this decision support, and it was mostly accomplished through static green-bar paper reports and some ad hoc querying. But in the last decade, the decision-support tools (data warehouse and business intelligence tools) have become more and more sophisticated for data access, data analysis, data manipulation, data mining, forecasting, trend analysis and other metric-based presentations such as scorecards and dashboards. Nowadays, they even include packaged analytical applications for specific business domains, such as supply chain analysis, sales channel analysis, performance analysis, etc. Data mining is a method of pattern discovery against a pool of data using specialized data mining tools. These tools use a sophisticated blend of classical and advanced components like artificial intelligence, pattern recognition, databases, traditional statistics, and graphics to present hidden relationships and patterns they find in any given data pool. One of the official definitions for data mining is: "Data analysis without preconceived hypothesis to unearth unsuspected or unknown relationships, patterns or associations of data." Simply put, "without preconceived hypothesis" means you don't know what exactly you are looking for, "to unearth" means the tool will analyze the data using special algorithms and analytical models to discover any patterns in the data and then tell you about them. The term data mining is sometimes misused to mean "ability to write a lot of different SQL queries."