Policy Brief January 2020 - Use Drives Quality - Considering Data Quality Issues in California’s Pursuit of a Cradle-to-Career Data System

Oct 15, 2026

Uploaded by Jacob

Policy Brief January 2020 examines data quality considerations in California’s effort to build a cradle-to-career (P20W) student data system. It explains how accuracy and completeness matter when using administrative records from schools, colleges, state agencies, and workforce data. The brief reviews the generally good quality of K-20 and workforce data, identifies common problem types such as missing, inaccurate, and inconsistent records, and discusses reasons quality can deteriorate, including misunderstanding questions, new data elements, evolving codes, and reporting interpretation differences.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages7

Reading Time18 min

AccessFree to download

Data Quality and the P20W System

California’s movement toward a statewide data system

Follow-up to the Education Insights Center series

Why Data Quality Matters

Accuracy and completeness in administrative records

Current Quality of K-20 and Workforce Data

Where quality is strongest

Types of quality problems

Examples of Known Inconsistencies

Program/course taxonomy codes

High school course admission requirements

Causes of Poor Data Quality

Misunderstanding survey or application questions

Newly collected information

Changes to data elements and codes

Reporting interpretation differences

POLICY BRIEF JANUARY 2020 Use Drives Quality: Considering Data Quality Issues in California’s Pursuit of a Cradle-to-Career Data System An addendum to the series: California Education Policy, Student Data, and the Quest to Improve Student Progress By Colleen Moore California is Moving Forward on a Data System California is taking steps toward building a statewide data system to support efforts to improve student progress and outcomes from preschool through higher education and into the workforce (known as a P20W data system) , a move recommended by numerous research, policy, and advocacy organizations over many years.1 The state’s Cradle-to-Career Data Workgroup comprises representatives of the public segments of K-12 and higher education, private colleges and universities, workforce development agencies, and agencies administering financial aid, health, and human services programs.2 The Workgroup will meet over the next 18 months to develop recommendations about the structure and function of a P20W data system, with input from advisory groups of educators, researchers, education advocates, and other stakeholders. The Education Insights Center produced a series of reports culminating in recommendations for the structure and governance of a P20W data system.3 This brief follows up on that series, with a focus on data quality; the brief was informed by the author’s experience using California’s existing education and workforce data systems to conduct research, as well as conversations with 14 researchers and other experts who have significant experience using those data to conduct research, to develop data tools for educators and the public, and for operational purposes.4 Data Quality is an Important Consideration Data quality, as discussed in this brief, refers to the accuracy and completeness of the data , which is an important consideration in the development of a P20W data system. Administrative records, like those maintained by schools, colleges, and state agencies for operational use, offer great opportunities as the foundation for a P20W data system. They allow for observation of individuals over time and across institutions, contain a broad array of information, and are comprehensive rather than representing a sample of individuals. All administrative records have some issues with inaccurate or incomplete information that can result from data entry errors, miscoding of information, and a number of other factors. However, with sufficient attention to assessing data quality, and appropriate steps to mitigate any issues through good data management, administrative records are uniquely valuable for informing decisions about policy and practice.5 Most K-20 and Workforce Data are of Good Quality The student records maintained by the California Department of Education (CDE) , California Community Colleges (CCC), California State University (CSU) , and University of California (UC) , as well as the employment and earnings records maintained by the Employment Development Department (EDD) , are fairly accurate and complete, with a level of quality problems no greater than would be expected in any large administrative data set. Not surprisingly, data elements that are routinely used for a particular purpose, such as the courses students enrolled in, the grades they earned, and the certificates or degrees they were awarded, are of higher quality than elements that serve little operational purpose for the institutions that collect them. Data used to allocate funding, to administer specific programs, or for reporting on accountability metrics are generally of good quality. The data quality problems that exist usually affect a small share of cases and are of several varieties, including: • missing data; • inaccurate data, such as codes in a data element that do not match the data element dictionary (the documentation that defines data elements and their codes) or responses that appear incorrect in the cont

FAQs

What does “data quality” mean in this brief?

It refers to the accuracy and completeness of data, which is critical to building and using a P20W data system. The brief emphasizes that administrative records can be valuable when data quality is assessed and managed well.

What kinds of data quality problems are discussed?

The brief highlights missing data, inaccurate data (such as codes that don’t match the data dictionary or responses inconsistent with related information), and inconsistent data such as mismatched identification numbers or demographics across records.

Why can data quality be poor when it occurs?

It can result from misunderstanding questions or response choices, delays in adopting newly added data elements, evolving data codes that require time to learn and apply, and differences in how institutions interpret what and how to report.

Oct 15, 2026

Uploaded by Jacob