The goal of the techniques of association is to identify the relationship or associations between the specific values of the categorical variables in the large data. This is very common in data mining subcategory text mining. These very powerful exploratory techniques have a large range of applications in diverse areas of business practices and also research. It helps the analysts to bring out or uncover the hidden patterns that are there in large data sets. The purpose is to address the distinguishing data mining problems
Sequence Analysis: The sequence analysis is related to the subsequent purchase of a product that has been bought already previously. However, the rules of sequence are not very apparent and the technique of sequence analysis helps in the extraction of such rules even if they are deeply hidden in the market database basket. Sequence analysis can be seen to have application in different areas of research such as shopping patterns, phone calls, DNA sequencing, variations in the stock market etc.
Link Analysis: Once the job of extraction has been done, the rules about the association or sequencing of items can be seen to have multiple benefits in application. Application of the link analysis and technologies to large data bases may simplify the task of extracting patterns and associations between the individuals and their actions. It would help to expose the structure of some clandestine illegal jobs.
Out of the box requirements for data analysis: Different cross tabulations, specifically the multiple response tables are used for the purpose of analysis of data. However, when the categories in the data are extremely large and when there is no knowledge of the factorial degree of the important association rules, then these kind of cross tabulations are very challenging to put to use or at times even not applicable.