Data Culture Toolkit: Data Quality Considerations

Resources to Assess Data Quality

Team members can use the following two resources when exploring and documenting issues and work related to data quality:
1. State-Level Data Quality Considerations Worksheet
2. Local-Level Data Quality Considerations Worksheet

The considerations presented here are intended to guide data team members in assessing the quality of the data they need to answer critical questions. Team members should apply their own knowledge and perspectives, think broadly about the data, and consider data quality issues. To ensure data quality, the individuals at the local and state levels who are most familiar with the data to be analyzed should be included in the discussions and the considerations used to develop the strategies.

The considerations are listed below. The letters (L or S) following each consideration suggest at which level the consideration might be used (local or state).

Data Quality Consideration

  1. After receipt of locally collected data, what standardized state data procedures have been developed, documented, and routinely implemented to address data quality? (For example, how are duplicate records from multiple local agencies handled? How are incomplete data handled? How are local agencies informed of potentially missing data? Are standardized procedures documented and regularly updated?) [S]
  2. What standardized local agency data procedures for collecting and entering data have been developed for: data entry, data entry qualifications and training, timelines for data entry, and data entry checks, etc.? Are those standardized procedures documented and regularly updated? [L]
  3. What [state or local] data governance structure and procedures are in place to support Part C or Part B 619 data quality? (e.g., a detailed data dictionary, decision-making authority, security and access)? [S, L]
  4. To what extent do [state or local] data systems have edit checks to help reduce or flag errors in the data? What additional edit checks might be beneficial? [S, L]
  5. How do [state or local] staff assess data quality issues? How do they know what to look for, how to assess data quality, and how to improve data processes? [S, L]
  6. What [state or local] data quality reports exist for staff to share with colleagues and other agencies for review, updates, and correcting data at the: child, building, district, region, and case load levels? [S, L]
  7. What state agency procedures are in place to support the local data staff and processes? (e.g., assigned state data stewards, formal timelines, available file naming conventions, established storage locations, support documents, FAQs, opportunities for stakeholder input, regular training for new and established local staff, and help desk.)? [S]
  8. How do local staff collaborate with the state staff to clean and edit data? Who, how, and when do local staff review and edit the submitted data? [S, L]
  9. What is the [state or local] staff capacity to recognize, understand, collect, and use the data? (e.g., child development, functional skills, and typical child development for child outcomes; use of assessment tools; established categories and decision trees for specific indicators)? [S, L]