Research Papers On Data Mining And Warehousing
Analysis of the data includes simple query and reporting, statistical analysis, more complex multidimensional analysis, and data mining.
Data analysis and data mining are a subset of business intelligence (BI), which also incorporates data warehousing, database management systems, and Online Analytical Processing (OLAP).
Data mining can be defined as the process of extracting data, analyzing it from many dimensions or perspectives, then producing a summary of the information in a useful form that identifies relationships within the data.
There are two types of data mining: descriptive, which gives information about existing data; and predictive, which makes forecasts based on the data.
A corporate data warehouse or departmental data mart is useless if that data cannot be put to work.
Data warehouses are usually separate from production systems, as the production data is added to the data warehouse at intervals that vary, according to business needs and system constraints.
As the complexity of data analysis grows, so does the amount of data being stored and analyzed; ever more powerful and faster analysis tools and hardware platforms are required to maintain the data warehouse.
A successful data warehousing strategy requires a powerful, fast, and easy way to develop useful information from raw data.
With the increasing data being produced each year, BI has become a hot topic.
The increasing focus on BI has caused a number of large organizations have begun to increase their presence in the space, leading to a consolidation around some of the largest software vendors in the world.