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CS614 GDB Solution & Discussion Due Date Feb 09, 2017

CS614 - Data Warehousing GDB No. 1 Solution Fall 2016 Due Date Feb 09, 2017 

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Graded discussion (GDB) will be launched on 8th February, 2017 and it will remain open for two days. You can post your comments on below mentioned topic till 9thFebruary, 2017.

Graded Discussion:

Scenario

Data mining and Data warehousing are inter-related but yet different areas in the field of Computer sciences. What is the major difference between these two and how they are related to each other?      

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Data Warehouse is an organized and well structured central repository.
But Data Mining aims to explore and examines the data through queries. These queries can be fired on Data Warehouse.
So the Data Warehouse and Data Mining are different in the context of aims.
Both are related to each other. Because the Data Mining uses the Data Warehouse to accomplish the purpose. Without the Data Warehouse the Data Mining can never be processed. And if we make the Data Warehouse and not done Data Mining on it then you are not taking benefit from Data Warehouse.

Data warehouse:
A database consists of one or more files that need to be stored on a computer. In large organizations, databases are typically not stored on the individual computers of employees but in a central system. This central system typically consists of one or more computer servers. A server is a computer system that provides a service over a network. The server is often located in a room with controlled access, so only authorized personnel can get physical access to the server.
In a typical setting, the database files reside on the server, but they can be accessed from many different computers in the organization. As the number and complexity of databases grows, we start referring to them together as a data warehouse.
Data Mining
Once all the data is stored and organized in databases, what's next? Many day-to-day operations are supported by databases. Queries based on SQL, a database programming language, are used to answer basic questions about data. But, as the collection of data grows in a database, the amount of data can easily become overwhelming. How does an organization get the most out of its data without getting lost in the details? That's where data mining comes in.

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Data warehouse:
A database consists of one or more files that need to be stored on a computer. In large organizations, databases are typically not stored on the individual computers of employees but in a central system. This central system typically consists of one or more computer servers. A server is a computer system that provides a service over a network. The server is often located in a room with controlled access, so only authorized personnel can get physical access to the server.
In a typical setting, the database files reside on the server, but they can be accessed from many different computers in the organization. As the number and complexity of databases grows, we start referring to them together as a data warehouse.
Data Mining
Once all the data is stored and organized in databases, what's next? Many day-to-day operations are supported by databases. Queries based on SQL, a database programming language, are used to answer basic questions about data. But, as the collection of data grows in a database, the amount of data can easily become overwhelming. How does an organization get the most out of its data without getting lost in the details? That's where data mining comes in.

CS614 GDB
Data Warehouse is an organized and well structured central repository.
But Data Mining aims to explore and examines the data through queries. These queries can be fired on Data Warehouse.
So the Data Warehouse and Data Mining are different in the context of aims. 
Both are related to each other. Because the Data Mining uses the Data Warehouse to accomplish the purpose. Without the Data Warehouse the Data Mining can never be processed. And if we make the Data Warehouse and not done Data mining on it then you are not taking benefit from Data Warehouse.

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