Analysis of text data is different to other types of data analysis such as numbers, dates, and time. The analysis of numeric and date/time datatypes can be done in a very definitive way. For example, if you are looking for all records with a price greater than or equal to 50, the result is a simple yes or no for each record. Either the record in question qualifies or doesn't qualify for inclusion in the query's result. Similarly, when querying something by date or time, the criteria for searching through the records is very clearly defined—a record either falls into the date/time range or it doesn't.
However, the analysis of text/string data can be different. Text data can be of a different nature, and it can be used for structured analysis or unstructured analysis.
Some examples of structured types of string fields are as follows: country codes, product codes, non-numeric serial numbers/identifiers, and so on. The datatype of these fields may be a string, but often...
