Large language models (LLMs) are all the rage, especially with recent developments from OpenAI. The allure of LLMs comes from their ability to understand, interpret, and generate human language in a way that was once thought to be the exclusive domain of humans. Tools like CoPilot are quickly integrating into the everyday life of developers, while ChatGPT-fueled applications are becoming increasingly mainstream. The popularity of LLMs also stems from their accessibility to the average developer. With many open-source models available, new tech startups appear daily with some sort of LLM-based solution to a problem.  Data has been referred to as the “ new oil .” In machine learning, data serves as the raw material used to train, test, and validate models. High-quality, diverse, and representative data is essential for creating LLMs that are accurate, reliable, and robust. Building your own LLM can be challenging, especially when it comes to collecting and storing data.…