Synthetic Data
Synthetic Data vs Data Masking: Benefits & Challenges in 2025
Data breaches cost organizations an average of $4 million globally, and by the end of 2025, 30% of critical infrastructure organizations are expected to face operation-halting security breaches. Protecting sensitive database information is more urgent than ever.
Synthetic Data vs Real Data: Benefits, Challenges in 2025
Synthetic data is widely used across various domains, including machine learning, deep learning, generative AI (GenAI), large language models, and data analytics. According to Gartner, by 2030, synthetic data use will outweigh real data in AI models.
Synthetic Data for Computer Vision: Benefits & Examples
Advancements in deep learning techniques have paved the way for successful computer vision and image recognition applications in fields such as automotive, healthcare, and security. Computers that can derive meaningful information from visual data enable numerous applications such as self-driving cars and highly accurate detection of diseases.
Top 20 Synthetic Data Use Cases & Applications in 2025
Synthetic data offers solutions to common challenges in data science, including data privacy concerns and limited dataset sizes. Synthetic data is gaining widespread popularity and applicability across industries, including machine learning, deep learning, generative AI (GenAI), and large language models. We listed the capabilities and most common use cases of synthetic data in different industries and departments/business units.
Top 5 Synthetic Data Finance Applications in 2025
In my eleven years of academic and professional experience, I observe that artificial intelligence has a diverse set of applications in financial services from process automation to chatbots and fraud detection.
Synthetic Data Generation Benchmark & Best Practices ['25]
We benchmarked 7 publicly available synthetic data generators sourced from 4 distinct providers, utilizing a holdout dataset comprising 70,000 samples, with 4 numerical and 7 categorical features, to evaluate their performance in replicating real-world data characteristics. Below, you can see the benchmark results where we statistically compare the synthetic data generators.