Misata: Outcome-Conformant Synthetic Data Generation

Muhammed Rasin

Synthetic Data for Education and EdTech

Describe a school or district, for example 6 schools with 3,000 students, and Misata Studio builds schools, teachers, students, class sections, enrolments, assessments and daily attendance. A student's age, grade and enrolment date come from one birth date, so they always agree; a class is taught by a teacher of its own school; and a letter grade follows the scores it summarises. An online course platform works too: describe it and Studio designs the tables for it.

Updated 2026-09-24.

You would write

A school district with 6 schools, 3,000 students, their teachers, classes, assessments and daily attendance for one school year.

Studio builds this on one of its tested archetypes: the mechanics below are fixed and verified, and what the business sells, the names and the wording are written for yours.

Start from this

What Studio builds

schools and teachersEach teacher belongs to one school

studentsAge, grade and enrolment date worked out from one birth date

classesTaught by a teacher of the class's own school

enrollmentsStudents only in classes of their own school

assessments and attendanceScores, letter grades that follow them, and daily attendance

What holds, and how you know

These are checked on the finished data, not assumed. Each dataset comes with a certificate listing what you asked for and whether it was met. How we verify.

A Grade 9 student is fourteen or fifteen, and joined after turning five
Teachers, classes and students never cross school lines
A letter grade follows the scores it summarises
Every foreign key points at a row that exists, checked on the finished data
Every count, total, rate, share and date window you state is applied exactly, or listed as not applied
A certificate lists each requirement and whether the data meets it

Have a schema, specialised rules or a large volume and would rather hand it off? Ask us to build it for you.

Frequently asked

Do I need real education data to generate this?

No. Misata Studio builds the dataset from a description, a schema you draw, or a structure you import (SQL DDL, DBML or a CSV header). No real records are uploaded, copied or learned from, so there is nothing to anonymise.

Is the generated education data privacy safe?

Yes. Nothing is learned from real records, so no real person, customer or account can appear in the output. A model writes names, places and wording, and Studio may research public facts on the web (you can turn research off). It never asks for your data.

Can I control the numbers, like rates and totals?

Yes. State a total, a monthly curve, a share or a rate in plain words, or draw the curve, and Studio applies it exactly. The certificate lists each figure and whether it was met. If a figure cannot be met, Studio says so instead of changing it.

Can I use my own schema?

Yes. Paste SQL DDL or DBML, import a CSV structure, or draw the tables on the canvas. A schema you give is followed exactly, and any difference is reported.

Which formats can I export?

CSV, Excel, Parquet, JSON Lines, SQL for Postgres, MySQL, SQL Server, Oracle, BigQuery and Snowflake, SQLite, DuckDB, dbt seeds, Prisma, DBML, TypeScript, JSON Schema, a data dictionary and more.

Choosing a tool? How Misata compares

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