In DWH loops may exist between the table. If loops exist, then query generation will take more time, because more than one path is available. It creates ambiguity also. Loops can be avoided by creating aliases of the table or by context.. i.e. defining execution path.

Data cleaning is a self explainatory term. Most of the data warehouses in the world source data from multiple systems - systems that were created long before data warehousing was well understood, and hence without the vision to consolidate the same in a single repository of information. In such a scenario, the possiblities of the following are there:
-> Missing information for a column from one of the data sources;
-> Inconsistent information among different data sources;
-> Orphan records;
->Outliar data points;
->Different data types for the same information among various data sources, leading to improper conversion;
->Data breaching business rules
In order to ensure that the data warehouse is not infected by any of these discrepencies, it is important to cleanse the data using a set of business rules, before it makes its way into the data warehouse.

Database is collection of inter related data. It is a storege place where the data is taken place.Database is the place where the data is taken as a base and managed to get avialable fast and efficient access.
Dataware house is typical relational database. Dataware house is the place where the application data is managed for analysis and reporting purposes.It is used for anlysing and quering business reqirements. It maintains historical data.