Data-Quality-10-Developer-Specialist Exam Dumps - Informatica Data Quality Questions and Answers

Never use First Name as it is not necessary

No standardization of First Name field is necessary

Use the Edit Distance strategy

Create Soundex or NYSIIS value for the First Name and use it in match

Consolidate duplicates into master record

Bad record management

Automatically consolidates data

ReGroup records for matching

There is no specific reason. It is simply a step of an ordered best practice approach.

It is good because it is easier to determine if a field is numeric or text.

Values with leading spaces or punctuation will typically sort to the top or bottom making them easier to identify.

None of the above.

Edit Distance

Bigram

Hamming Distance

Jaro Distance

In Excel, choose to Add a service and either enter the URL address or select the .wsdl or .xml file to be imported.

Build and Test a web Services Mapping in the Developer Tool.

Export the Mapping to PowerCenter and test.

Create and Deploy the mapping as an Application.

Data Rules must be run against the entire data set they are defined upon

Once created a Data Rule cannot be changed...it can only be deleted and re-created

A Data Rule created in the Analyst will appear as a mapplet with an Expression Transformation in the Developer

Data Rules can only be run on data in the project in which they were created

Scorecarding

Matching

Grading

Standardization

The Developer can only review Profiles created by the Analyst but can not create any profiles themselves

The Developer can take Analyst built profiles with rules and generate a mapping ensuring lossless translation of Information between specification and Implementation.

Comments, Tags and Rules can only be applied to profiles in the Analyst Tool

Only one Tag can be applied to each object in a project.

The Address Validator transformation searches the address reference data and returns all addresses that are possible matches with the input address.

The Address Validator transformation searches the address reference data and returns the most likely candidate address.

The Address Validator transformation parses data into the suggested address fields without performing validation.

The Address Validator transformation will return various cleansed standardized versions of the input record for the user to choose from.

Standardization converts data to standardized formats

Standardization can remove "noise"

Standardization corrects and automatically updates the data in your source system

Standardization can remove or replace bad or inconsistent data