5 (685) · $ 7.50 · In stock
In this article, the author discusses the importance of using synthetic data in data analytics projects, especially in financial institutions, to solve the problems of data scarcity and more importantly data privacy.
In this article, the author discusses the importance of using synthetic data in data analytics projects, especially in financial institutions, to solve the problems of data scarcity and data privacy.
The 8 Most Challenging Data Privacy Issues (and How to Solve Them)
A software engineering perspective on engineering machine learning systems: State of the art and challenges - ScienceDirect
Data Scarcity and using Synthetic Data to overcome it
The Synthetic Solution: Overcoming Data Scarcity in Machine Learning, by Harshita Sharma, Accredian
Data Analytics - InfoQ
Overcoming Data Scarcity and Privacy Challenges with Synthetic Data - InfoQ
Data Analysis - InfoQ
Privacy Data Security - FasterCapital
Beyond GDPR: Navigating Data Privacy Challenges with Synthetic Data
A Copy Worth More Than the Original?
Overcoming Data Consumption Challenges with Data Products