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According to Watson (2000) ‘data warehouse is a tools of information technology management that helps business decision makers to instant access of information of customer data throughout the organisation by combining all database and operational systems like sales and transaction, human resource, inventory, purchasing, financial and marketing system. Data warehouse pull out, clean, convert and manage large volumes of data from various systems and creating a historical record of all customer'.

Data warehousing technology is the most crucial part of CRM because it makes CRM possible. Shepard et al. (1998) said ‘a better understanding of customer behaviour is possible because data warehousing technology consolidates correlates and convert customer data into customer intelligence. Thoughts of customers and their buying pattern can improve information relating to customer service interactions, bill and account status, back orders, product returns, product delivery, and internal operating cost. The capacity of a data storehouse to store hundreds and thousands of gigabytes of data compose an analysis feasible as well as immediate.

Organisational benefits with a data warehouse are as follows;

exact and faster access of information

bad and duplicate data eliminate by quality data and filtering

customer profiling and retention modelling

it compute total present importance and approximate future value of every customer

it gives detail report

2.7 DATA MINING TECHNOLOGY

Peppers and Rogres, (1999) said that ‘the first analytical step of data mining is to describe the data. Data mining summarize its statistical attributes like standard deviations and means, visually review it by use of charts and graphs and distributes the value of the field in our data. But alone data description can not provide an action plan. We have to build a analytical model based on pattern determined from known output and after that we have to test the model on result outside the original sample. An ideal model must never be puzzled with reality, but it is useful guide to understanding our businesses'.

According to Eckerson and Watson (2000) ‘we can use data mining for both classification and regression problems. In first problem we can predict what type something will fall into. In second problems we are predicting a number like prospect that a person will react to an recommend. In CRM process, data mining is often used to allocate a score to a particular customer. Data mining is also often using to recognize a set of characteristics, which is called profile. Data mining segments customers in to groups with similar behaviour like purchasing a particular product.'

2.8 THE CRM PROCESS CYCLE IN BANKS

Pound (2000) said that exploration and alteration process should be done by the banks on basis of customer information captured; this shows the full value of CRM initiatives. Banks set up a closed CRM cycle with the help of an integrated CRM solution, which composed of a set of continuous iterative process. It manages the whole customer related process for bank, analysing cust本论文由英语论文网提供整理，提供论文代写，英语论文代写，代写论文，代写英语论文，代写留学生论文，代写英文论文，留学生论文代写相关核心关键词搜索。