Data Warehouse and Data Mining Overview

First. Concept questions
1. What is the definition of data warehouse?
A: data warehouse is a topic oriented, integrated, stable data collection at different times, which is used to support the decision-making process of the operation and management center.
2. What are the characteristics of data warehouse?
A: the characteristics of data warehouse are:
(1) data warehouse is subject oriented;
(2) data warehouse is integrated;
(3) data warehouse is stable;
(4) data warehouse changes with time;
(5) large amount of data in data warehouse;
(6) the requirements of data warehouse software and hardware are high.
3. What is business intelligence?

A: Based on the database, business intelligence helps enterprise leaders make fast and accurate decisions in response to the changing market environment through online analytical processing and data mining technology.

Second. Short answer questions
1. The difference and connection between data warehouse and data mining.
Difference:
Data warehouse is a kind of storage technology, its data storage capacity is 100 times of general database, it contains a lot of historical data, current detailed data and comprehensive data. It can adapt to different users to provide data and information for different decision-making needs.
Data mining is developed from artificial intelligence machine learning. It studies all kinds of methods and technologies, and extracts useful information and knowledge from a large number of data.
Contact:
Data warehouse and data mining are both new decision support technologies. But they have totally different ways of supporting decision-making. Data warehouse stores a large number of decision-making data, which provides different users with random query, comprehensive information or trend analysis information. Data mining is to use a series of algorithms to mine the hidden information and knowledge in data, so that users can use them in decision-making.