Download

Data transformation involves processes that alter data structure, format, and sometimes data values to improve consistency and usability of customer data.

Transforming and standardising your customer data provides additional value inputs can significantly improve your understanding of your customers, drive better business outcomes, and contribute to sustainable growth in today’s data-driven business landscape.

Our transformation libraries contain over 370,000 data points to help you… Abbreviate, Elaborate, Exclude, or Normalise your data within MS Excel.

Choose from 5 spoken languages (English, Spanish, French, German, and Italian) and 11 different transformation categories, including: Business, Countries, First Names, and Addressing.

That,Is,How,It,Works.,Smiling,Businesswoman,Experienced,In,Work

Transform Use Case Examples

The transfromation examples below are shown in English.

Abbreviate
Abbreviate Transformation Examples

Abbreviate, when selected, allows you to transform the structure of your data to ensure a consistent format. 

For example, you can choose to Abbreviate business elements in a company name field. This will reduce ‘Limited’ to ‘Ltd’, ‘Group’ to ‘Grp’, ‘Incorporated’ to ‘Inc’ etc. and write the results directly back to the field you select in your data set. 

Category Example 
Addressing ‘Road’ to ‘Rd’, ‘Avenue’ to ‘Ave’ 
Business ‘Limited’ to ‘Ltd’, ‘Company’ to ‘Co’ 
Countries ‘United Kingdom’ to ‘UK’, ‘New Zealand’ to ‘NZ’ 
DateEvents ‘January’ to ‘Jan’, ‘Monday’ to ‘Mon’ 
JobTitles ‘Manager’ to ‘Mgr’, ‘Colonel’ to ‘Col’ 
Numbers ‘Twenty’ to ’20’, ‘Nine’ to ‘9’ 
Qualifications ‘Bachelor of Science’ to ‘BSc’, Doctor of Philosophy to ‘Phd’ 
Salutations ‘Doctor to Dr’, ‘Mister’ to ‘Mr’ 
WeightsMeasures ‘Ounces’ to ‘Oz’ 
Miscellaneous ‘Object’ to ‘Obj’ 
Elaborate
Elaborate Transformation Examples

Elaborate your data to ensure a consistent long form output. 

If you choose to elaborate business elements. This will expand ‘Ltd’ to ‘Limited’, ‘Grp’ to ‘Group’, ‘Inc.’ to ‘Incorporated’ etc. and write the results directly back to the attribute selected in your data set. 

Category Example 
Addressing ‘Rd’ to ‘Road’, ‘Ave’ to ‘Avenue’ 
Business ‘Ltd’ to ‘Limited’, ‘Co’ to ‘Company’ 
Countries ‘UK’ to ‘United Kingdom’, ‘NZ’ to ‘New Zealand’ 
DateEvents ‘Jan’ to ‘January’, ‘Mon’ to ‘Monday’ 
JobTitles ‘Mgr’ to ‘Manager’, ‘Col’ to ‘Colonel’ 
Numbers ‘9’ to ‘Nine’, ’20’ to ‘Twenty’ 
Qualifications ‘Bsc’ to Bachelor of Science, ‘Phd’ to Doctor of Philosophy 
Salutations ‘Dr’ to ‘Doctor’, ‘Mr’ to ‘Mister’ 
WeightsMeasures ‘Oz’ to ‘Ounces’ 
Miscellaneous ‘Obj’ to ‘Object’ 
Forenames ‘Bob’ to ‘Robert’, ‘Tony’ to ‘Anthony’ 
Exclude
Exclude Transformations Examples

Exclude your data to remove unnecessary or unwanted values. 

For example, you can choose to exclude business elements in a company name field. This will remove ‘Ltd’, ‘Limited’, ‘Grp’, ‘Group’, ‘Inc’, ‘Incorporated’ etc. 

Category Example 
Addressing Exclude text such as ‘Road’ and ‘Rd’ 
Business Exclude text such as ‘Ltd’ and ‘Limited’ 
Countries Exclude text such as ‘UK’ and ‘USA’ 
DateEvents Exclude text such as ‘Mon’ and ‘January’ 
JobTitles Exclude text such as ‘Mgr’ and ‘Manager’ 
Numbers Exclude text such as ‘100’ and ‘Hundred’ 
Qualifications Exclude text such as ‘BA’ and ‘BSc’ 
Salutations Exclude text such as ‘Mr’ and ‘Dr’ 
WeightsMeasures Exclude text such as ‘Oz’ and ‘Ounces’ 
Miscellaneous Exclude text such as ‘Obj’ and ‘Object’ 
Forenames Exclude text such as ‘Andi’ and ‘Robert’ 
Normalise
Normalise Transformation Examples

Elaborate your data to ensure a consistent long form output 

Normalise your data to ensure a consistent short form output.  For data cleansing, this is less safe than abbreviate, however, useful for record matching purposes. 

For example, you can choose to normalize business elements in a company name field. This will like abbreviate reduce ‘Limited’ ‘Ltd’ to, and ‘Group’ to ‘Grp’ and ‘Incorporated’ to ‘Inc’ etc. and write the results directly back to the field you select in your data set. 

Category Example 
Addressing ‘Garden’, ‘Garden’, ‘Gdns’ to ‘GDN’ 
Business ‘Company’, ‘Comp’ to ‘CO’ 
Countries ‘United Kingdom’, ‘Great Britain’, ‘GBR’ to ‘GB” 
DateEvents ‘January’ to ‘Jan’, ‘Monday’ to ‘Mon’ 
JobTitles ‘Engineer’, ‘Engr’ to ‘ENG’ 
Numbers ‘Nought’, ‘Null’, ‘Nil’ to ‘0’ 
Qualifications ‘Dr of Philosophy’, ‘DPhil’ to ‘PhD’ 
Salutations ‘Mrs’, ‘Ms’, ‘Madam’ to ‘MRS’ 
WeightsMeasures ‘Inches’, ‘Inch’, ‘Ins’ to ‘IN’ 
Miscellaneous ‘Cheque’, ‘Check’ to ‘Chq’ 
Forenames ‘Andrew’, ‘Andrea’, ‘Andres’ to ‘Andi’ 

 

Transliteration
Transliteration of Characters Example

Transliterate will change international diacritics like.. ‘á’, ‘é’, ‘í’, ‘ó’, ‘ú’, to their equivalent non-diacritic values e.g. ‘a’, ‘e’, ‘i’, ‘o’, ‘u’.

Another example is changing the German sharp ‘s’ character ‘ß’ to ‘ss’.

Business Benefits of Transforming your Customer Data:

Better Marketing ROI
Improved Data Consistency for Enhanced Customer Insight
Efficient Data Integration
Reduced Errors and Redundancies
Improved Customer Relationships
Cost Savings: By reducing error

Why Transform Data in Excel?

Utilise Comprehensive Transformation Libraries

Access our extensive transformation libraries housing over 370,000 data points. Within MS Excel, abbreviate, elaborate, exclude, or normalise data seamlessly across 11 different transformation categories and in 5 spoken languages (English, Spanish, French, German, and Italian).

Maximised Marketing Returns

Transformed data leads to improved targeting and precision in marketing efforts, thus maximising ROI by reaching the right audience with tailored messages.

Driving Business Outcomes Through Transformation

Standardising and transforming customer data delivers invaluable inputs, fostering a deeper understanding of customers. This, in turn, drives better business outcomes, fostering sustainable growth in today’s data-centric business landscape.

Error Reduction and Improved Relationships

Data transformation minimises errors and void fields, fostering more accurate customer profiles. This accuracy contributes to stronger customer relationships built on trust and reliability.

Solutions

Company

Country

Job Title

Location

Person

Install DQ for Excel within minutes for complete control over your customer data.

This is how easy it is:

Make an Enquiry

Product and account support