Data Integrity Initiative

Data Integrity Toolkit

The need to understand Data and Sample Integrity extends across all sectors of the  Insights and Analytics industry, including Data & Sample Providers to Users & Decision Makers. Building awareness of data integrity issues should be broad to include not only traditional marketing research and sample provider companies, but also end-users across a wide variety of client-side industries and verticals. There is a need to elevate basic understanding and evaluation of data integrity issues for all end users, while at the same time, ensuring transparency and discipline among sample and data providers. To fully benefit the industry, sample and data integrity definitions, quality measures and evaluation processes should continuously evolve and extend to as many research methodologies as needed. In addition, familiarity with professional standards and certifications is important for elevating overall knowledge of potential solutions for achieving data and sample integrity.
DI Toolkit Industry Resources

   

   

Glossary of Terms

            

Data Quality and Fraud terms for both Quantitative and Qualitative related to:

     1. Respondent characteristics relating to data quality
     2. Behavior and biases relating to problematic respondents
     3. Tools and methods for detecting problematic respondents
     4. Characteristics of panels and samples that can affect data quality
     5. Issues relating to survey design that can affect data quality
     6. Terms relating to the validation of fraud-detection solutions

     7. General terms

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     Data Quality Measurement and Evaluation

The DII Toolkit includes Measurement and Evaluation approaches that can be used within a “Code of Conduct” for best practices across our industry. Adoption across broad stakeholder groups allows for continuous improvement across all data quality areas. Guides on selecting data suppliers and providers, designed specifically for end-users and decisionmakers, are also shown below. In addition, the Insights Association’s DII Council has created the Checks of Integrity framework that can guide providers and users of research on key data integrity measures and evaluations needed across all phases of survey research.

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Guidelines for Assessing Quality


The DII Toolkit includes guidelines for assessing data quality for your research projects.  Ensuring data quality begins with COLLABORATION across all key stakeholders. 

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Professional Standards and Certifications

             

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Advocacy and Policy

 

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