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Synthetic data generators for tabular and time-series data

Generate relevant synthetic data quickly for your projects. The Databricks Labs synthetic data generator (aka `dbldatagen`) may be used to generate large simulated / synthetic data sets for test, POCs, and other uses in Databricks environments including in Delta Live Tables pipelines

DataGenerator is a Java library for systematically producing large volumes of data. DataGenerator frames data production as a modeling problem, with a user providing a model of dependencies among variables and the library traversing the model to produce relevant data sets.

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Automatically generate data for an object

🐙 Generate mock data effortlessly from TypeScript interfaces in a web application powered by Next.js and NextUI.

🎲 RandomGen for PowerToys Run Generate random data instantly with a single keystroke

This script is designed to convert bodies of text into a question and answer JSON format using the GPT-4 language model. The process involves extracting text from PDF files, tokenizing the text, generating questions and answers, and then saving the results in a JSON file.

Python application to write stock security data to a MongoDB Cluster. Supports a variable amount of stocks, variable amount of time and can write to a MongoDB time-series collection

Datagenerator for Data Services