Data Mining Techniques (Mini Project
3.1 NECESSITY OF DATA MINIING
Data is numbers or text which is a statement of a fact. It is unprocessed and stored in database for further analysis. Operational and transaction data such as cost and sales, is essential to modern enterprise's internal environment. Non-operational data such as competitors' sales and forecasting data, is responsible for analysis of external environment.
Information is generated through data mining so that it becomes useful, meaningful and specific. Information mostly are relationships, patterns and associations among the huge pool of data. Those information obtained from data mining can be used for forecasting or auditing.
Data mining is a process of sorting and picking out meaningful and useful information from a large pool of data. Through data mining we can identify the trends or patterns of the data, thus we can propose a corresponding and optimum plan for the enterprise.
Nowadays, company stored massive data for their future since the competitive environment is rigorous. They have to know more about the competitive forces which can be competitors, new entrants, suppliers, customers and competitive rival from 5-forces model of competitive environment. They used data mining techniques to identify any trend or pattern among their data. Mostly the data warehouse take over this function.
Moreover, nowadays enterprise are affected by financial crisis adversely, they are more likely to undertake lean strategy which means we need the datelining techniques to identify operational activity.
For Boly's case, we acknowledged there was abundant unprocessed data of VIP customers and it is hand-written. It is useless if we just keep it unprocessed. In order to help Boly to understand the market and buying behavior of their customers, Data mining is necessary to process the data into relevant information that would show the pattern of the market or buying