Synthetic Data: Shaping the Future of AI and Data Science
Source: Gartner In the rapidly evolving landscape of AI and data science, synthetic data is emerging as a key driver of innovation. As real-world data becomes increasingly difficult to access due to privacy laws, high costs, and logistical constraints, synthetic data offers a compelling alternative — one that is private, scalable, and customizable. At DataGlimpse Technologies , we view synthetic data not just as a workaround, but as a foundational resource for future-ready business solutions. As a student-led, MSME-certified B2B startup, we are focused on building intelligent, scalable, and privacy-respecting tools for modern enterprises. Understanding Synthetic Data Synthetic data refers to data that is artificially generated rather than collected from real-world events. It is created using mathematical models, simulations, and advanced AI techniques such as Generative Adversarial Networks (GANs) and large language models (LLMs) . Despite being artificial, synthetic data reta...