Designed to provide assistance to IDEA Part C Data Managers and other users of the EDFacts Metadata and Process System (EMAPS). This tool offers a way to ensure accuracy of IDEA Part C Child Count and Settings data prior to official submission. The Part C Child Count and Setting Data Tool allows the state to enter their data and have any errors flagged. Corrections can then be made prior to data entry and submission in EMAPS.
Part C Data Managers are shifting timelines and processes in response to new deadlines around modernization. Dates have been updated to reflect the most recent information (May 2024) from the EDFacts Partner Support Center.
Updated for 2024! We asked DaSy experts for tools that are helpful for this season and for ways to prepare for what’s ahead.
Stay focused with these quick tips for State Performance Plan/Annual Performance Report (SPP/APR) season for Part C Data Managers, Coordinators and staff.
Conference: Early Childhood Inclusion Institute Date: May 2023 Presenters: Grace Kelley, Ginger Elliott-Teague, Sally Shepherd A facilitated discussion among participants to map a path to improving understanding of the scope […]
Save time by identifying potential format errors, validation errors, and other errors in subtotals or totals before data for submission via EMAPS.
Part C Data Managers are shifting timelines and processes in response to new deadlines around modernization. Top Part C Data tasks to tackle this quarter are focused around OSEP’s modernization of the data submission system.
Overview Data Leadership Competencies Data Foundations Data Analysis Data Use & Sharing Introduction Data Quality Basics: Understanding Data Quality Data Quality Basics: Validity and Reliability Common Part C and Part […]
Overview Data Leadership Competencies Data Foundations Data Analysis Data Use & Sharing Introduction Data Quality Basics: Understanding Data Quality Data Quality Basics: Validity and Reliability Common Part C and Part […]
Overview Data Leadership Competencies Data Foundations Data Analysis Data Use & Sharing Introduction Data Quality Basics: Understanding Data Quality Data Quality Basics: Validity and Reliability Common Part C and Part […]