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Data Marts and Data Mining



Today\'s corporations strive to conduct their business on a national and global basis. Business expansion creates the need to access corporate data from different geographical locations in a timely manner. To meet this demand, smaller versions of the data warehouse based on certain criteria, called data marts can be created.
The figure below shows how the architecture changes to accommodate the introduction of data marts:

Figure 2 - Data Marts

Some companies use data marts to complement their data warehouses by moving data into them from the data warehouse allowing for more efficient analysis. Some corporations completely replace the concept of having a data warehouse with that of having smaller data marts that can be fed with the data they need from the operational systems.



No matter what the solution is, data marts usually have similar characteristics to those of the data warehouse, except for the data volume.
Data Mining
One relatively new, but powerful, concept that has started to gain popularity in the business intelligence (BI) world is data mining. With data mining, managers find out aspects and facts about their business that may not be evident otherwise. Data mining works on top of a data warehouse, making use of its contents in order to establish relationships between business elements that may seem completely unrelated.
Data mining helps discovering unknown associations, sequences - where one event leads to another later event. It leads to recognizing patterns that lead to classification or new organization of data, forecasting and much more.