Deep Mirroring: The Ultimate Proof-of-Concept Tool and How it Works

What is Deep Mirroring - prooV

Or, everything you wanted to know about prooV’s patented deep mirroring technology but were afraid to ask.


What is deep mirroring? 

Deep mirroring, prooV’s patented technology, automatically generates data that mimics the patterns and behaviors of your real production data, for use when evaluating third-party software. It gives you all the benefits of running a proof-of-concept with real data — such as evaluating how solutions perform in your specific production environment — but with none of the risks. You can easily generate millions of records to populate your PoC testing environments with very little of your original data (data sample). 

Does deep mirroring output data preserve the original data properties? 

Absolutely. Deep mirroring is designed to fully maintain data integrity, including relationships, logical and physical data types, functional dependencies. 

Can any type of data in any form be extrapolated? 

prooV supports data of a numeric or textual type. Other types of data such as blobs are not supported yet. 

Optional: Anonymizing the data sample

Sometimes even the data sample may not be shared, even for extrapolation. Therefore, we developed a complementary SDK to create fully-anonymized data samples and ensure that the transformed data maintains its integrity. Users may apply other anonymization tools as long as it does not break the links and the patterns within your datasets. 

deep mirroring explained - prooV

What are the anonymization strategies that prooV SDK applies? 

  • RandomBoolean 
  • RandomBooleanOneZero 
  • RandomBooleanFrueFalse 
  • RandomBooleanYN 
  • DateRandomDelta 
  • DateTimeRandomDelta 
  • RandomEmail 
  • PickFromDatabase 
  • PickFromFile PickFromList 
  • AddressStrategy from addresses.txt 
  • CreditCardStrategy 
  • TakeFromDatabaseStrategy – takes reference data from DB via a provided SQL 
  • SELECT DateRandomShiftStrategy 
  • DateShiftStrategy 
  • DatetimeRandomShiftStrategy 
  • DatetimeShiftStrategy 
  • RandomDatesInRangeStrategy 
  • RandomDatetimesInRangeStrategy 
  • RecordBasedEmailStrategy 
  • RandomFemaleFirstNameStrategy 
  • RandomMaleFirstNameStrategy 
  • BoundedDoubleStrategy 
  • BoundedFloatStrategy BoundedIntStrategy 
  • FixedDoubleDeltaStrategy 
  • FixedFloatDeltaStrategy 
  • FixedIntDeltaStrategy 
  • UkPhoneNumberStrategy 
  • IbanStrategy 
  • RecordBasedExclusion 
  • RegexpTemplateStrategy 
  • SwiftBicStrategy 
  • UuidTemplateStrategy 
  • VehicleRegistrationNumber

The bottom line 

Deep mirroring offers a unique solution to all who want to thoroughly evaluate new software before integrating it into the enterprise system – with all its valuable data, vulnerable structures  –  while keeping the regulatory environment in mind.

Can I deep mirror my sample data? 

Of course! Request a demo or email [email protected] and a member of our team will help you extrapolate a small subset of data. 

Deep Mirroring CTA - proov

About the author

Pamela is VP Marketing @prooV