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Enterprise Resource Planning
notes
figure 2.5: Data mining chart
Data mining is a technique based on construction of data warehousing. Data warehousing stores
a huge amount of archive data whereas data mining process this data into valid and potentially
useful information. This information could be further, used to make certain important decisions.
The data mining systems considers previous history of investigated system, testing hypothesis
about the rules; when concise and valuable knowledge about the system has been discovered, it
should be incorporated into decision support system which helps the managers or executives to
make the business decisions.
The problems like inadequacy of human brain while searching for complex data and lack of
objectiveness in analyzing it, could be avoided by using computerized automated systems for
analysis of huge amount of data. The automated data mining systems also reduces the cost of
hiring the highly trained professional technicians.
The data mining system is a user – friendly system; it simplifies the job and allows an analyst to
manage the process of extracting knowledge and meaningful information from data.
Data mining should be applicable to any kind of data repository, as well as to transient data,
such as data streams. The data repository may include relational databases, data warehouses,
transactional databases, advanced database systems, flat files, data streams, and the Worldwide
Web. Advanced database systems include object-relational databases and specific application-
oriented databases, such as spatial databases, time-series databases, text databases, and
multimedia databases. The challenges and techniques of mining may differ for each of the
repository systems.
A brief introduction to each of the major data repository systems listed above.
flat files
Flat files are actually the most common data source for data mining algorithms, especially at the
research level. Flat files are simple data files in text or binary format with a structure known by
the data mining algorithm to be applied. The data in these files can be transactions, time-series
data, scientific measurements, etc.
34 LoveLy professionaL university