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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.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/policy-brief-january-2020-use-drives-quality-considering-data-quality-issues-in-californias-pursuit-of-a-cradle-to-career-data-system/583563/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/policy-brief-january-2020-use-drives-quality-considering-data-quality-issues-in-californias-pursuit-of-a-cradle-to-career-data-system/583563.png","ImageObject",300,407,{"name":92,"@type":93},"Jacob","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":29},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What does “data quality” mean in this brief?","Question",{"text":112,"@type":113},"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.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What kinds of data quality problems are discussed?",{"text":117,"@type":113},"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.",{"name":119,"@type":110,"acceptedAnswer":120},"Why can data quality be poor when it occurs?",{"text":121,"@type":113},"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.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},583563,1792230788,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":29,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":34,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144,"preview_page_count":4},962084931830,"https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd","POLICY BRIEF JANUARY 2020  \nUse Drives Quality: Considering Data Quality Issues in California’s Pursuit of a Cradle-to-Career Data System  \nAn addendum to the series:  \nCalifornia Education Policy, Student Data, and the Quest to Improve Student Progress  \nBy Colleen Moore  \nCalifornia is Moving Forward on a Data System  \nCalifornia 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.  \nThe 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  \nData Quality is an Important Consideration  \nData 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  \nresult 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  \nMost K-20 and Workforce Data are of Good Quality  \nThe 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.  \nThe data quality problems that exist usually affect a small share of cases and are of several varieties, including:  \n• missing data;  \n• 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","cbCaiscg1WVvb5r9","https://ap.wps.com/l/cbCaiscg1WVvb5r9","pdf",948396,"English","# Data Quality and the P20W System\n## California’s movement toward a statewide data system\n## Follow-up to the Education Insights Center series\n# Why Data Quality Matters\n## Accuracy and completeness in administrative records\n# Current Quality of K-20 and Workforce Data\n## Where quality is strongest\n## Types of quality problems\n# Examples of Known Inconsistencies\n## Program/course taxonomy codes\n## High school course admission requirements\n# Causes of Poor Data Quality\n## Misunderstanding survey or application questions\n## Newly collected information\n## Changes to data elements and codes\n## Reporting interpretation differences","[{\"question\":\"What does “data quality” mean in this brief?\",\"answer\":\"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.\"},{\"question\":\"What kinds of data quality problems are discussed?\",\"answer\":\"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.\"},{\"question\":\"Why can data quality be poor when it occurs?\",\"answer\":\"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.\"}]","Policy Brief January 2020 - Use Drives Quality - Considering Data Quality Issues in California’s Pursuit of a Cradle-to-Career Data System | PDF",1792047700,18]