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Unit 2: ERP and Related Technology
Some of the advance data warehousing system supports to produce reports as well as on – line notes
analysis, multidimensional analysis of the data.
characteristics of Data Warehousing
According to Bill Inmon, author of Building the data Warehouse and the guru who is widely
considered to be the originator of the data warehousing concept, there are generally four
characteristics that describe a data warehouse:
1. Subject oriented: Data are organized according to subject instead of application e.g. an
insurance company using a data warehouse would organize their data by customer,
premium, and claim, instead of by different products (auto, life, etc,). The data organized
by subject contain only the information necessary for decision support processing.
2. Integrated: When data resides in many separate applications in the operational environment,
encoding of data is often inconsistent. For instance, in one application, gender might be
coded as “m” and “f” in another by 0 and 1. When data are moved from the operational
environment into the data warehouse, they assume a consistent coding convention e.g.
gender data is transformed to “m” and “f”.
3. Time variant: The data warehouse contains a place for storing data that are five to 10
years old, or older, to be used for comparisons, trends, and forecasting. These data are not
updated.
4. Non volatile: Data are not updated or changed in any way once they enter the data
warehouse, but are only loaded and accessed.
Task Data warehouse is a concept related to storage. What about executive
information system?
2.12 Data mining
Today, in industry, in media, and in the database research milieu, the term data mining is becoming
more popular than the longer term of knowledge discovery from data. Therefore in a broader
view of data mining functionality data mining can be defined as “the process of discovering
interesting knowledge from large amounts of data stored in databases, data warehouses, or other
information repositories.”
For many years, statistics have been used to analyze data in an effort to find correlations, patterns,
and dependencies. However, with an increased in technology more and more data are available,
which greatly exceed the human capacity to manually analyze them. Before the 1990’s, data
collected by bankers, credit card companies, department stores and so on have little used. But
in recent years, as computational power increases, the idea of data mining has emerged. Data
mining is a term used to describe the “process of discovering patterns and trends in large data
sets in order to find useful decision-making information.” With data mining, the information
obtained from the bankers, credit card companies, and department stores can be put to good
use.
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