# Infosys Whitepaper 
Title: Test data management in software testing life cycle- Business need and benefits in functional, performance, and automation testing 
Author: Infosys Limited 
Format: PDF 1.7 

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 WHITE PAPER TEST DATA MANAGEMENT IN  SOFTWARE TESTING LIFE CYCLE- BUSINESS NEED AND BENEFITS IN  FUNCTIONAL, PERFORMANCE,   AND AUTOMATION TESTING Praveen Bagare (Infosys) and Ruslan  Desyatnikov (Citibank) 

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 Abstract The testing industry today is looking  for ways and means to optimize  testing effort and costs.  One potential  area of optimization is test data  management. Testing completeness  and coverage depends mainly on the  quality of test data. It stands to reason  that without high quality data testing  assurance is unattainable. A test plan  with several comprehensive scenarios  cannot be executed unless appropriate  data is available to run the scenarios.<|endoftext|>The best data is found in production  since these are actual entries the  application uses. While using  production data, it is always prudent  to create a sub-set of the data. This  reduces the effort involved in test  planning and execution and helps  achieve optimization.  However, live  data is not always easily available for  testing. Depending on the business,  privacy and legal concerns may be  associated with using live data. Often  the data is not complete and therefore  cannot be used for testing.  It is best to  avoid the use of raw production data  to safeguard business and steer clear  of expensive lawsuits.  The challenge of TDM lies in obtaining  the right data effectively. Before  proceeding on this path, we need  to find answers to some pertinent  questions: Will there be a positive  return on the investment? Where  do we start implementing Test  Data Management (TDM)? Should  we start with functional testing or  non-functional testing?  Can test  automation help?   The practice of not including TDM  steps in the Testing Life Cycle often  leads to ignorance towards TDM on  part of the testing team. This paper  attempts to explain why testers in  the functional, non-functional and  automation test arenas need the  TDM service. We also discuss the test  data challenges faced by testers and  describe the unparalleled benefits of a  successful TDM implementation.<|endoftext|>TDM is fast gaining importance in the  testing industry. Behind this increasing  interest in TDM are major financial losses  caused by production defects, which could  have been detected by testing with the  proper test data. Some years ago, test  data was limited to a few rows of data in  the database or a few sample input files.  Since then, the testing landscape has come  a long way. Now financial and banking  institutions rely on powerful test data sets  and unique combinations that have high  coverage and drive the testing, including  negative testing. TDM introduces the  structured engineering approach to test  data requirements of all possible business  scenarios.  Large financial and banking institutions  also leverage TDM for regulatory  compliance. This is a critical area for these  institutions due to the hefty penalties  associated with non-compliance. Penalties  for regulatory non-compliance can run into  hundreds of thousands of dollars or more.  Data masking (obfuscating) of sensitive  information and synthetic data creation  are some of the key TDM services that can  assure compliance.<|endoftext|>Significance of Test Data Management External Document © 2018 Infosys Limited 

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 Test data is any information that is used  as an input to perform a test. It can  be static or transactional. Static data  containing names, countries, currencies,  etc., are not sensitive, whereas data  pertaining to Social Security Number  (SSN), credit card information or medical  history may be sensitive in nature.  In addition to the static data, testing  teams need the right combination of  transaction data sets/conditions to test  business features and scenarios.  TDM is the process of fulfilling the test  data needs of testing teams by ensuring  that test data of the right quality is  provisioned in suitable quantity, correct  format and proper environment, at the  appropriate time. It ensures that the  provisioned data includes all the major  flavors of data, is referentially intact and  is of the right size. The provisioned data  must not be too large in quantity like  production data or too small to fulfill all the  testing needs. This data can be provisioned  by either synthetic data creation or  production extraction and masking or by  sourcing from lookup tables.<|endoftext|>TDM can be implemented efficiently with  the aid of well-defined processes, manual  methods and proprietary utilities. It can  also be put into practice using well-evolved  TDM tools such as Datamaker, Optim or  others available in the market.<|endoftext|>A TDM strategy can be built based on the  type of data requirements in the project.  This strategy can be in the form of: •  Construction of SQL queries that  extract data from multiple tables in the  databases • Creation of flat files based on:    Mapping rules      Simple modification or desensitizing  of production data or files     An intelligent combination of all of  these What is Test Data  Management? External Document © 2018 Infosys Limited 

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 Some of the most common challenges  faced by testing teams while sourcing test  data are: •  Test data coverage is often incomplete  and the team may not have the required  knowledge.<|endoftext|>•  Clear data requirements with volume  specifications are often not gathered  and documented during the test  requirements phase.<|endoftext|>•  Testing teams may not have access  to the data sources (upstream and  downstream).<|endoftext|>•  Data is generally requested from the  development team which is slow to  respond due to other priority tasks.<|endoftext|>•  Data is usually available in large chunks  from production dumps and  can  be sensitive in nature, have limited  coverage or may be unsuitable for the  business scenarios to be tested.<|endoftext|>•  Large volumes of data may be needed  in a short span of time and appropriate  tools may not be at the testing team’s  disposal.<|endoftext|>•  Same data may be used by multiple  testing teams, in the same environment,  resulting in data corruption.<|endoftext|>•  Review and reuse of data is rarely  realized and leveraged.<|endoftext|>•  Testers may not have the knowledge of  alternate data creation solutions using a  TDM tool.<|endoftext|>•  Logical data relationships may be hidden  at the code level and hence testers may  not extract or mask all the referential data.<|endoftext|>•  Data dependencies or combinations to  test certain business scenarios can add  to the difficulties in sourcing test data.<|endoftext|>•  Testers often spend a significant amount  of time communicating with architects,  database administrators, and business  analysts to gather test data instead  of focusing on the actual testing and  validation work.<|endoftext|>•  A large amount of time is spent in  gathering test data.<|endoftext|>•  Most of the data creation happens  during the course of execution based on  learning.<|endoftext|>•  If the data related to defects is not found  during testing, it can cause a major risk  to production.<|endoftext|>The Challenges of Test Data  Sourcing External Document © 2018 Infosys Limited 

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 TDM Offers Efficient Solutions and  Valuable Benefits  An effective TDM implementation can address most of the challenges mentioned above. Some of the key benefits  that a business can gain by leveraging the TDM services are: Superior quality Minimum time Reduced cost Less resources •  Optimal data coverage is  achieved by the TDM team  through intelligent tools and  techniques based on data  analysis strategies •  The TDM service employs a  dedicated data provisioning  team with agreed service-level  agreements (SLAs) ensuring  prompt data delivery •  Condensed test design and  data preparation effort helps  achieve cost savings •  Database or file access provided  to the TDM team facilitates data  privacy and reuse  •  Test data requirements from  the TDM team enable the  testing team to capture these  effectively during the test  planning phase. Version- controlled data requirements  and test data ensure complete  traceability and easier  replication of results •  Compact test design and  execution cycles can be  achieved for reduced time to  market •  Minimized test data storage  space leads to reduction of  overall infrastructure cost •  Professionals with specialized  skills, sharp focus on Test  Data and access to industry  standard tools contribute to  the success of TDM •  Detailed analysis and review  of data requirements ensure  early identification of issues  and resolution of queries •  Automated processes lead to  less rework and reduced result  replication time •  The TDM team also wears  the system architect’s