What is the difference between data mining and datawarehouse with example?
Answers
Answer :
- Comparison between data mining and data warehousing:
Data Warehousing:-
1)A data warehouse is database system which is designed for analytical analysis instead of transactional work.
2)Data is stored periodically.
3)Data warehousing is the process of extracting and storing data to allow easier reporting.
4)Data warehousing is solely carried out by engineers.
5)Data warehousing is the process of pooling all relevant data together.
Data Mining:-
1)Data mining is the process of analyzing data patterns.
2)Data is analyzed regularly.
3)Data mining is the use of pattern recognition logic to identify patterns.
4)Data mining is carried by business users with the help of engineers.
5)Data mining is considered as a process of extracting data from large data sets.
Explanation:
Data Warehousing:
It is a technology that aggregates structured data from one or more sources so that it can be compared and analyzed rather than transaction processing. A data warehouse is designed to support management decision-making process by providing a platform for data cleaning, data integration and data consolidation. A data warehouse contains subject-oriented, integrated, time-variant and non-volatile data.
Data Mining:
It is the process of finding patterns and correlations within large data sets to identify relationships between data. Data mining tools allow a business organization to predict customer behavior. Data mining tools are used to build risk models and detect fraud. Data mining is used in market analysis and management, fraud detection, corporate analysis and risk management