Synthetic Data Generation: A New Challenge in the Data Management Scenario

Synthetic data are artificially generated data, that is, information that does not come from direct observations of the real environment, but is obtained using advanced computational techniques. These data are generated from statistical and machine learning algorithms, capable of creating distributions and characteristics similar to those observed in real data sets, preserving key statistical patterns without containing sensitive or identifiable information.

Synthetic data generation is emerging as a powerful tool to address data privacy, accessibility, and scalability challenges in today’s data management landscape. At the Data Management Summit, this roundtable will examine the role of synthetic data in training models, enhancing data security, and enabling innovation. While synthetic data offers promising solutions, it also introduces complexities around data quality, governance, and ethical considerations.

Key topics of discussion will include:

Join industry leaders and data professionals to explore the opportunities and challenges of synthetic data generation, and discover how organizations can responsibly integrate synthetic data into their data management strategies to drive secure, innovative, and efficient outcomes