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Data Warehousing and Data Mining  
 
 

Data Warehousing is the process of combining data from multiple and varied sources into one comprehensive database and which accessed from central location. Data warehouses store current as well as historical data and are used for creating reports such as annual and quarterly comparisons. Data warehouse environment includes extraction, transportation, transformation, and loading, online analytical processing (OLAP) engine, client analysis tools, and other applications that manage the process of gathering data and delivering it to users. Common accessing systems of data warehousing include queries, analyzing and reports. Data warehouses can be subdivided into data marts. Data marts store subsets of data from a warehouse. Data warehousing concerned with some applications such as Agriculture, Biological data analysis, Call record analysis, Decision support, financial forecasting, Logistics and Inventory management.

Data Mining is the process of analyzing data from different perspectives and summarizing it into useful information and finding patterns or extracting hidden patterns from large amounts of data among fields in large relational databases. Data mining software has a number of analytical tools for analyzing data. Data mining techniques are used in a many research areas, including mathematics, cybernetics, genetics and marketing. Data mining is all about the extracting information from a data set and transforms it into an understandable structure for further use.


Some Benefits of a data warehouse are:

1. Maintain data history, even if the source transaction systems do not.

2. Integrate data from multiple source systems, enabling a central view across the enterprise.    This benefit is always valuable, but particularly so when the organization has grown by      merger.

3. Improve data quality, by providing consistent codes and descriptions, flagging or even fixing    bad data. Present the organization's information consistently.

4. Provide a single common data model for all data of interest regardless of the data's source.

5. Restructure the data so that it makes sense to the business users

 

Data mining consists of five major elements

1. Extract, transform, and load transaction data onto the data warehouse system

2. Store and manage the data in a multidimensional database system

3. Provide data access to business analysts and information technology professionals

4. Analyze the data by application software

5. Present the data in a useful format, such as a graph or table

 

Data mining tasks Includes

1. Anomaly detection

2. Dependency modeling

3. Clustering

4. Classification

5. Regression

6. Summarization

 

Courses and Eligibility

1. Student must pass higher secondary education or 10+2 with science subjects to get    admission into bachelor’s degree program

2. B.E in Computer science or Information Science

3. B.Tech in Computer Applications

4. MCA in Computers

5. M.Tech in Computers

 

 
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