Data mining is the
process of finding patterns from large data sets and analyzing data from
different perspectives. It allows business users to analyze data from different
angles and summarize the relationships identified. Data mining can be useful in
increasing the revenue and cut costs.
Example:
In a supermarket, the persons who bought the tooth brush on Sundays also bought tooth paste. This information can be used in increasing the revenue by providing an offer on tooth brush and tooth paste. There by selling more number of products (tooth paste and tooth brush) on Sundays.
Data mining process:
Data mining analyzes relationships and patterns in the stored data based on user queries. Data mining involves four tasks.
Example:
In a supermarket, the persons who bought the tooth brush on Sundays also bought tooth paste. This information can be used in increasing the revenue by providing an offer on tooth brush and tooth paste. There by selling more number of products (tooth paste and tooth brush) on Sundays.
Data mining process:
Data mining analyzes relationships and patterns in the stored data based on user queries. Data mining involves four tasks.
·
Association: Find the
relationship between the variables. For example in retail a store, we can
determine which products are bought together frequently and this information
can be used to market these products.
·
Clustering:
Identifying the logical relationship in the data items and grouping them. For
example in a retail store, a tooth paste, tooth brush can be logically grouped.
·
Classifying: Involves in
applying a known pattern to the new data.