Description

DRAFT and IN PROGRESS

The Sample Data Generator produces (SDG) realistic, cohesive, and 100% yet fictional datasets for use in demonstrations and testing.  , testing and other scenarios useful to Ed-Fi implementations, without using actual data.  The Sample Data Generator is provided as an executable and as source code.

The SDG prefers statistically realistic patterns (e.g., a student with poor attendance generally tracks to poor grades, students are the appropriate age for their grade level, students who are English learners have home languages that track to their ethnicity, and so forth). The system is configurable, and can produce arbitrarily large datasets.

While the SDG creates data with realistic patterns, it is randomly generated and must not be used in place of real-world data for scenarios such as training for machine learning or other algorithmic approaches.

Download

• Code : ((GitHub https://github.com/Ed-Fi OSS repo link))-Alliance-OSS/Ed-Fi-SampleDataGenerator
• ZIP Package:  ((GitHub Release ZIP package link))https://github.com/Ed-Fi-Alliance-OSS/Ed-Fi-SampleDataGenerator/archive/refs/tags/DS-3.2a.zip
• Documentation:  Sample Data Generator

Details

• By: Major contributions from EdWire; base from Ed-Fi
• License Terms: Apache 2.0 License
• Released: February 2022