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Data Products: 5 Deadly Sins and How To Prevent Them
The document discusses the five deadly sins in the context of data products: pride, wrath, lust, gluttony, and sloth, emphasizing the potential pitfalls in data product development. It highlights the importance of understanding user intent, responsible development practices, and maintaining continuous data pipelines. The presentation aims to guide data scientists in avoiding common mistakes and improving their systems.
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Data Products: 5 Deadly Sins and How To Prevent Them
- 1. DATA PRODUCTS: 5DEADLY SINS AND HOW TO PREVENT THEM Pride Wrath Lust Gluttony Sloth Mathieu Bastian Web Summit 2015, Dublin Credits:The Seven Deadly Sins, Nanatsu noTaizai & nimbus-mage.deviantart.com
- 2. ABOUT ME • Datascientist & engineer • Led data products team at LinkedIn • Gephi co-founder • Open-source contributor 2
- 3. DATA PRODUCTS Source: http://bit.ly/1kMUPAe. Tentativedefinition User-facing production system based on an automated learning algorithm 3
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- 5. PRIDE "Excessive belief inone’s own abilities or excessive love of oneself" 5
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- 7. With power comesresponsibility 7 Source: http://www.economist.com/node/15579717
- 8. Who are youbuilding it for? Understand user intent Integrate into the user flow Explain recommendations to the user Set right user expectations Treat user like you would like to be treated 8 Credits: Google
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- 10. WRATH “Choice of violentand hateful actions over love and patience" 10
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- 12. Exercise perseverance Reward Time Phase II: Growth PhaseIII: Maintenance Phase I: Inception 12
- 13. But have aplan 13
- 14. LUST "Depraved thought, unwholesome moralityand desire for excitement" 14
- 15. LUST Credits: Google DataCenter 15
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- 17. Thank the janitor& handyman 17
- 18. GLUTTONY "The consumption ofmore of anything than you need" 18
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- 20. Avoid solo datascientists 20 Credits: Lucasfilm
- 21. Choose the rightproblem M - Measurable E - Explainable R - Rapid prototyping C - Core I - Iterable 21
- 22. SLOTH "Not caring aboutothers or living life in a fulfilling way" 22
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- 24. Embrace continuous datapipelines Source: http://http://azkaban.github.io/ 24
- 25. Make data pipelinesrobust Code Upload Run workflow Look at logs Code Upload Run workflow PigUnit 25
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