Key Needs for most Data Management Project

Thoughts and Key Strategies for Test Data Management:

Data Acquisition

  • Data Profiling and Distribution
    • Data that includes confidential or sensitive information can still be shared, however. There are a number of steps researchers can take to protect subjects’ privacy2:
      • withholding part of the data
      • statistically altering the data in ways that will not compromise secondary analyses
      • requiring engineers who seek data to commit to protect privacy and confidentiality
      • providing data access in a controlled site, sometimes referred to as a data enclave.
  • How is it provided
    • The data have its own device name and data name. The data is stored in a separate file with binary format. Each file has “n” number of columns for data, which generally represent various data features.
    • from stored historical data
    • Active systems / projects
      • from dynamic / fresh data
    • Web site/platforms
    • Mobile / OTA
  • Automated, Tool or Manual Data Preparation
    • Automated Accelerators
    • Tools such as Informatica, etc.
    • Manual teams – most used – and can be up to 40-50% of the project spend
    • defining test data
      • to be used in a test case,
      • copying or creating test data,
      • securing or masking sensitive data,
      • and so on—are taking up more than half a developers’ and QA team’s time during the testing phase.
  • Data Integrity
    • Data must be archived in a controlled, secure environment in a way that safeguards the primary data, observations, or recordings.
    • The archive must be accessible by engineers analyzing the data, and available to collaborators or others who have rights of access
    • Primary data should be stored securely for sufficient time following publication, analysis, or termination of the project.
    • The number of years that data should be retained varies from field to field and may depend on the nature of the data and the research.
    • Keeping data partitioned and limited to view by assigned groups
  • Data Maintenance and Refresh
    • When determining the appropriate storage format for  data, consider
      • What will you do with your data once you acquire it?
      • Will you write and read data with the same application?
      • How much data will you acquire?
      • At what rate will you acquire data?
      • Will you need to exchange data with another program?
      • Will you need to search your data files?
  • Data Governance
    • Rules and Policies for testing phases and teams
    • How is it used

Without Test Data Management

Define Test Data Requirements

  • Tester Efficiency
    • Cost Per Test Cycle = $2.7M
    • 100 Days, 300 Testers, $90/hour
    • 20% application defects due to bad test data
  • Application quality
    • Cost of a defect found later in the release cycle = XX

With TDM

Define Test Data Requirements

  • Improve Tester Efficiency by 30%                                         Improve Tester Efficiency by > 30%
    • Cost Per Test Cycle = $1.6M                                           Reduce Testing cycles by > 25%
    • 60 Days, 300 Testers, $90/hour                                       Improve application quality by 90% Tester Efficiency
    • 90% reduction in test data-related defects
    • Cost avoidance

ref: Informatica “Why Do You Need Test Data Management?” 
ref: Forrester Report:  “http://tealium.com/assets/pdf/Forrester_Boost_Digital_Intelligence.pdf

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