Description: The research paper Data Warehousing and Data Mining Final Year Seminar Topic talks about information explosion- the rate at which data is churned out and effective ways of securing the data. If data mining secures the data, data warehousing manages the data into accessible formats and makes it available in a prudent format that allows decision making in a quick and easy way.
The research paper talks about predictive data mining as the most efficient and productive types. The paper also talks about the three major responsibilities undertaken by the data mining process they are:
- Exploration
- Model building and pattern formation going hand in hand with validation/verification
- Deployment ( prediction ensues this stage)
The research paper talks about the crucial aspects of data mining. They are
- Bagging
- Data reduction
- Data preparation
- Deployment
Models of data mining have been suggested in the research paper. They are:
- CRISP
- Six Sigma
- Predictive data mining
Data warehousing is a process in which data is arranged in prudent formats that allows sensible decision making in no time. Data warehousing aims at making the decision making process ‘On-line’. The most effective data warehousing architecture will be incorporating or at least referencing all data available in the relevant enterprise-wide information management systems, using designated technology suitable for corporate data base management (e.g., Oracle, Sybase, MS SQL Server.
Conclusion: The research paper concludes on a note that although data mining and data warehousing techniques have revolutionized data management systems, there are many loopholes that cannot go unmentioned. There are many inherent and external threats that render the flow of data and securing it vulnerable. There are many effective techniques and applications that have been mentioned in the research paper already. Nevertheless both data mining and data warehousing have miles to go. The applications have to be considered solely from performance perspective.
Download Data Warehousing and Data Mining Final Year Seminar Topic.