Measurecamp Brussels - Synthetic data.pdf
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This document provides an overview of synthetic data by discussing what it is, why it is used today, and how it can potentially be used in the future. Specifically: - Synthetic data refers to artificially generated data that mimics real-world data statistically without containing personal information. - Today, synthetic data is commonly used for testing analytics setups, training teams using realistic data scenarios with no privacy risks, and creating product demos. - Potential future uses discussed include using synthetic data for algorithm development and differential privacy techniques.
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Conversations play an important role in building these relationships, but they are increasingly taking on digital forms, which are very hard to track. These conversations hold valuable information, but how can companies extract actionable insights? What role does Conversational Intelligence play?
Listen to an interview that Founder & CEO Neil Movold did with B2M's Simon Fawkes on the subject of Conversational Intelligence and the answers to these questions.
https://b2m.co.nz/conversational-intelligence/
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Measurecamp Brussels - Synthetic data.pdf
- 1. Synthetic data What, why & how Glenn Vanderlinden Human37 Measurecamp Brussels, December 2nd 2023
- 2. 2 Glenn Vanderlinden 🤖 Co-founder Human37 📆 Consulting, analytics & digital advertising since 2012 🧠CDPs, analytics, privacy & customer data 🤷 No technical background | Autodidact | Learning by breaking things Hi, I’m Glenn
- 3. 3 Context – Curious about the privacy engineering space, asking questions, trying stuff. This is the story of me exploring synthetic data. ✅Sharing of (unfinished) ideas ✅Experimental applications 🎯Inspiration 🙅Use this as input not the truth About this talk
- 4. 4 What is synthetic data? Synthetic data refers to artificially generated data that mimics the statistical properties and patterns of real-world data, without containing any personally identifiable information (PII) or sensitive details. Synthetic data, in the context of analytics, is an artificially created dataset that closely resembles real-world data while maintaining privacy. It is generated using algorithms, models, and statistical methods to replicate the attributes, distributions, and relationships found in actual data.
- 5. 5 Why do we use synthetic data today? 1. Testing – Conduct tests to validate analytics setups, customer journeys and personalisation workflows. 2. Training teams – Train with data that closely resembles use cases / business cases with zero risk of exposing actual customer data. 3. Product demos – Mock up entire scenarios and provide a visual representation of the results in real time.
- 6. 6 6 How do we use synthetic data?
- 7. 7 7 How do we use synthetic data?
- 8. 8 8 How do we use synthetic data?
- 9. 9 9 How do we use synthetic data?
- 10. 10 10 How do we use synthetic data?
- 11. 11 11 How do we use synthetic data?
- 13. 13 Why do we use synthetic data tomorrow? 1. Algorithm development – Create data sets to train models and algorithms. 2. Differential privacy