Case Study: Large Enterprise Banking Company

Explore case studies from verified users of Informatica Data Quality / Data Integration.

Challenges

  • Solved the following operational challenges by deploying Data Validation testing for PowerCenter:
    • Time-consuming manual regression testing
    • Not having an audit trail for testing
    • Not reporting on errors

Use Case

  • Currently using Data Validation testing for PowerCenter:
    • Deploying in an ongoing basis in development and QA (Unit/Regression testing)
  • Rated the following Data Validation testing for PowerCenter capabilities compared to alternatives they considered:
    • Automation: Better
    • Integration with PowerCenter: Better
    • Repeatability: Better
    • Auditability: Better

Results

  • Top purchasing drivers for buying Data Validation testing for PowerCenter:
    • Reduce overall cost associated with data testing
    • Reduce turn-around time for catching and fixing data quality issues
  • Rated the following benefits of purchasing Data Validation testing for PowerCenter:
    • Reduces total cost associated with data testing: Beneficial
    • Increases productivity for IT staff: Beneficial
    • Reduces total time dedicated to data testing: Beneficial
  • Increased the productivity of their IT staff by 20-39% with Data Validation testing for PowerCenter.
  • Reduced total time for data testing by 30-50% as a result of using Data Validation testing for PowerCenter.

Case Study 2

PURPOSE

The purpose of this document is to understand the ‘Basic transformations’ available in PowerCenter 7.1. These ‘Transformations’ are vital to development of mappings which carry the information how to extract, transform and load data. Thisdocument covers following Transformations based on a running hands-on Case-Studyconceiving the use of all these transformations. The Case-Study is divided in parts basedon some underlying concept covering one or more transformations at one time. Thetarget definitions developed in one mapping may be used as source definition in anothermapping to continue the concept and complete the whole case-study.The Basic Transformations covered through this document are:

  • FILTER TRANSFORMATION
  • JOINER TRANSFORMATION
  • SORTER TRANSFORMATION
  • EXPRESSION TRANSFORMATION
  • SOURCE QUALIFIER TRANSFORMATION
  • AGGREGATOR TRANSFORMATION
  • LOOKUP TRANSFORMATION

SCENARIO

Conceive a database build around the transactions at a chain of departmentalstores. The typical activities at stores include – maintaining customers information,maintaining employees information and the kind of job they perform, the itemsinformation available at the store along with promotion information, the sales and orders,procuring information with manufacturers and distributors.Thus the database has typically the following table structure:

  • CUSTOMERS
  • EMPLOYEES
  • STORES
  • MANUFACTURERS
  • JOBS
  • DEPARTMENT
  • ITEMS
  • PROMOTIONS
  • ITEMS_IN_PROMOTIONS
  • DISTRIBUTORS
  • ORDERS
  • ORDER_ITEMS

PROBLEM STATEMENT

Consider that our objective here is to get the information of the amount of salesdone by the chain of departmental stores. Herein we try to know the ‘Total Cost’ of itemssold for each Order (i.e. the amount of transactions done in each order) along with otherOrder details. The ‘Order cost’ is the sum of all the ‘items cost’ in the order with discountadjustments if any. The final target table should reflect the Total Cost against eachOrder_ID with other Order details. The intermediate target tables can be used as thesource for subsequent mappings.Though in a real scenario, target may be much bigger and will have large numberof tables and huge amounts of data in a very organized way to satisfy varied complexqueries, we are here safely assuming our final target contains only one table with exactlynecessary data to satisfy above query.

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