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  1. Preface
  2. Getting Started Overview
  3. Getting Started with Informatica Analyst
  4. Getting Started with Informatica Developer
  5. Frequently Asked Questions

Getting Started Guide

Getting Started Guide

Data Quality and Profiling

Data Quality and Profiling

Use the data quality capabilities in the Developer tool to analyze the content and structure of your data. You can enhance the data in ways that meet your business needs.
Use the Developer tool to design and run processes that achieve the following objectives:
  • Profile data. Profiling reveals the content and structure of your data. Profiling is a key step in any data project as it can identify strengths and weaknesses in your data and help you define your project plan.
  • Create scorecards to review data quality. A scorecard is a graphical representation of the quality measurements in a profile.
  • Standardize data values. Standardize data to remove errors and inconsistencies that you find when you run a profile. You can standardize variations in punctuation, formatting, and spelling. For example, you can ensure that the city, state, and ZIP code values are consistent.
  • Parse records. Parse data records to improve record structure and derive additional information from your data. You can split a single field of freeform data into fields that contain different information types. You can also add information to your records. For example, you can flag customer records as personal or business customers.
  • Validate postal addresses. Address validation evaluates and enhances the accuracy and deliverability of your postal address data. Address validation corrects errors in addresses and completes partial addresses by comparing address records against reference data from national postal carriers. Address validation can also add postal information that speeds mail delivery and reduces mail costs.
  • Find duplicate records. Duplicate record analysis compares a set of records against each other to find similar or matching values in selected data columns. You set the level of similarity that indicates a good match between field values. You can also set the relative weight fixed to each column in match calculations. For example, you can prioritize surname information over forename information.
  • Create and run data quality rules. Informatica provides pre-built rules that you can run or edit to suit your project objectives. You can create rules in the Developer tool.
  • Collaborate with Informatica users. The rules and reference data tables you add to the Model repository are available to users in the Developer tool and the Analyst tool. Users can collaborate on projects, and different users can take ownership of objects at different stages of a project.
  • Export mappings to PowerCenter. You can export mappings to PowerCenter to reuse the metadata for physical data integration or to create web services.

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