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Measurecamp Brussels - Synthetic data.pdf

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Synthetic data
What, why & how
Glenn Vanderlinden
Human37
Measurecamp Brussels, December 2nd 2023
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
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
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
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
How do we use synthetic data?
Ad

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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