Data Mining is the area of research which means digging of useful information or knowledge from previous data. There are different techniques used for the data mining. Data mining may used in different fields including Healthcare. Heart or Cardiovascular diseases are the very hot issue in Healthcare industry globally. Many patients died due to insufficient amount of knowledge. As Healthcare industry produces a huge amount of data, we may use data mining to find hidden patterns and interesting knowledge that may help in effective and efficient decision making. Data mining in Healthcare is a crucial and complicated task that needs to be executed accurately. It attempts to solve real world health problems in diagnosis and treatment of diseases. This work is also an attempt to find out interesting patterns from data of heart patients. There are three algorithm used with two different scenarios. These implemented algorithms are Decision Tree, Neural Network and Na

The Data Warehouse is the advanced form of the database which is used for decision-making by the executives. There are several front-end tools for data warehouse available to support decision making. These tools come under the categories such as OLAP, Data Mining and Enterprise Information System etc. The common thing in using these tools is to have knowledge about the schema. The users of decision-making systems are top management or executives who are normally non-technical having less knowledge of the data warehouse schema and about writing database technical queries. Therefore, Natural Language (NL) interface can facilitate the executives in their decision-making process. The users prefer to have an easy querying tool that free them from technicalities of back-end processes and let them focus on desired results.
This motivated us to develop a natural language retrieval system (Natural Language Interface to Data Warehouse) that supports users especially in the ad-hoc query development. Using this system, non-technical users can easily write any ad-hoc information need in their native language. Users without having the knowledge about back-end query processing and schema can retrieve any information they want that is available in Data Warehouse. As a result, the complexity and time is reduced as well as dependency is removed.