Define the process of Data Profiling, Data Cleansing and Data Enrichment.

Data Profiling:
Data Profiling is the process of examining the data available in an existing data source and collecting statistics and infrmatio about the data. The purpose of these statistics may be to :

1. Find out whether existing data can easily be used for other purpose.
2. Five metrics on data quality including whether the data conforms to company standards.
3. Access the risk involved in integrating data for new aplications, including the challenges of joins
4. Track data quality.
5. Access whether metadata accurately describes the actual values in the source database.

Data Cleansing:

Data cleansing or Data Scrubbing is the act of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database.

Data cleansing involves the following tasks: 

1. Converting data fields to common format 
2. Correcting errors 
3. Eliminating inconsistencies 
4. Matching records to eliminate duplicates 
5. Filling missing values etc. 

After cleansing, a data set will be consistent with other similar data sets in the system.

Data Enrichment 

Data Enrichment is the process of adding value to your data. In some cases, external data providers sell data, which may be used to augment existing data. In other cases, data from multiple internal sources are simply integrated to get the “big” picture. In any event, the intended result is a data asset that has been increased in value to the user community.