Synthetic vs. Augmented Data: What You Need to Know For Powerful Personalization
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Synthetic vs. Augmented Data: What You Need to Know For Powerful Personalization
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このコンテンツについて
Personalization at scale takes data - and a lot of it. In this episode we explore types of data that can can be “home grown” to help create ever more powerful and personalized experiences. In particular we dive into the concepts of synthetic and augmented data and their implications for technology and human experience.
Resources
AWS’ Guide To Data Augmentation - https://aws.amazon.com/what-is/data-augmentation/
Synthetic Data Generation using LLM: Crash Course for Beginners - https://youtu.be/hMjtdECXlYo?si=AHLaad4fj13VlG2N
Synthetic Data and the Future of AI - https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4722162
Personalization Done Right (Spotify Case Study) - https://hbr.org/2024/11/personalization-done-right
Takeaways
Synthetic data mimics statistical properties of real data.
Augmented data enriches existing data sets for better insights.
Context is crucial when utilizing data for decision-making.
Collaboration with data scientists enhances data utilization.
Synthetic data allows for scaling and running simulations.
Augmented data can personalize experiences across various industries.
Data limitations can hinder effective personalization efforts.
Elasticity testing can benefit from larger synthetic data sets.
Understanding different data types is essential for professionals.
The implications of data types extend to healthcare and user experience.
Chapters
00:00 - Introduction to Synthetic and Augmented Data
03:18 - Understanding Augmented Data
06:35 - Exploring Synthetic Data
09:18 - Applications of Augmented Data
12:08 - The Intersection of Data and Personalization
15:15 - Conclusion and Future Implications