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In this series of modules, you will use IBM InfoSphere FastTrack to create an application that identifies customers with high value to your business. You will. InfoSphere FastTrack provides capabilities to automate the workflow of your data integration project. Users can track and automate multiple. IBM InfoSphere FastTrack accelerates the design time to create source-to-target mappings and to automatically generate jobs. Mappings and jobs are then.

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You will experience how InfoSphere FastTrack increases the ease and efficiency by which you create mapping specifications.

Scenario for mapping data

For this tutorial, you will follow a fictional scenario about the First Midwest company. First Midwest is a financial institution that grew by infospuere. As First Midwest focused on acquisition activities, their competition pulled away several of their high-value customers. These customers were neglected or not treated preferably at First Midwest. Now the priority of First Midwest is to regain its customer base by improving its view of customer data.

First Midwest defines two levels of high-value customers. First Midwest wants to ensure that gold customers are offered new investment opportunities and that platinum customers are given premium customer service when they call in with issues.

The following components and applications must be installed on your system.

In Module 1, you prepare for the tutorial. First Midwest has these subsidiaries: BANK 1 Holds only checking accounts. The data is in one table: BANK 2 Holds checking and savings accounts. The data is in these tables: Customers might have checking and savings accounts. Therefore, account balances for both checking and savings accounts must be infosphsre to compute the total account balance for a customer.


Bank 2 also keeps track of demographic data about customers in a separate table, BANK2. BANK 3 Holds only savings accounts. The following steps illustrate the sequence of actions: First Midwest created a standard customer database that its subsidiaries use to represent customer data. You will access this database in Module 1, in Lesson 1. Through the modules, you create specifications and build an application to identify gold and platinum customers for marketing and customer service.

The application moves customer information from the bank subsidiaries into a standardized customer model. The standardized information is used to build information about platinum customers for the customer service department and information about gold customers for marketing.

Tutorial: IBM InfoSphere FastTrack Facilitated mapping creation

You then integrate the customer data from the Infosphefe 3 subsidiary into the database containing the standardized customer information. These ihfosphere are reflected in Figure 1. First Midwest subsidiaries and the plan for how the data flows. These tasks are required to build the application that identifies high-value customers:: Identify gold customers as level B and platinum customers as level A.

Standardize customer name and address information and add a business term that defines a level of service. Move gold customer data appropriate for marketing such as name, address, and gender from the bankdemo. You also can fasttrqck reports that provide details about mapping specifications that you create as you create the application. Learning objectives By completing the modules, you will learn about these functions: Create mapping specifications that map data from the source to the target tables.


Generate jobs that are used to build applications Generate reports to view mapping specifications statistics and characteristics.

Time required In the first module, you set up your environment, and the time required depends on your current environment. The remaining modules each take about minutes to complete. System requirements The following components and applications must be installed on your system. Modules in this tutorial Module 1: Set up the tutorial environment You must prepare your system to run the tutorial. Extract customer information from the BANK1 database In this module, you begin to consolidate relevant customer data into a table that follows the standard model of the company.

Extract customer information from the tables in the BANK2 schema The customer information that First Midwest wants to integrate into its banking system is in multiple tables. In this module, you perform a join, add source columns based on lookup operators, and define business rules before you extract the customer information.

Scenario for mapping data

Standardize information, use business terms, and create data extractions for customer marketing and service In this module, you associate customer data with business terms and create data extractions for marketing and customer service.

Integrate data from Bank 3 While fasytrack resolved issues with data in the Bank 1 and Bank 2 subsidiaries, the executive board at First Midwest acquired a new bank, Bank 3. Now you must integrate the customer data from Bank 3.