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UID:pretalx-europython-2024-M9TMMQ@programme.europython.eu
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DESCRIPTION:Ever felt like you’re navigating a data jungle\, battling to 
 survive the unexpected production problems that throw you off track? Well\
 , you’re not alone. Staying on top of your data's health is not just sma
 rt – it's crucial. In this talk\, I will share some Python tricks (metho
 ds and libraries) that you can use to defend from those wild data problems
 . Because let's face it\, being able to effectively monitor your data\, sp
 ot sneaky anomalies\, and get to the bottom of them is the key to unlockin
 g a buried treasure.\n\nFirst\, I'll take you through the ins and outs of 
 observability\, highlighting its importance for managing both the inputs a
 nd outputs of machine learning models\, as well as for overall data qualit
 y. We'll explore a range of techniques to detect anomalies\, with a focus 
 on multivariate time series data. We'll also cover how we can keep this pr
 ocess as computationally efficient as possible.\n\nBut we won't stop at ju
 st finding these anomalies: we're on a mission to chase them down to their
  lair! The second part of the talk will equip you with the detective skill
 s to perform root cause analysis and extract as much insights as possible.
  These discoveries can be an eye opener and the first step towards new pro
 jects and strategies. Next\, we will also tackle distinguishing real anoma
 lies from data evolution (or drift) and set up effective monitoring strate
 gies to keep your data clean and insightful.\n\nIf your interests lie in m
 achine learning or you're simply keen on data quality\, join me as we set 
 off to unravel the mysteries of data observability. Let's learn how to kee
 p data problems in check and when life gives you anomalies\, turn them int
 o business opportunities!
DTSTAMP:20260518T001443Z
LOCATION:North Hall
SUMMARY:One analysis a day keeps anomalies away! - Madalina Ciortan
URL:https://programme.europython.eu/europython-2024/talk/M9TMMQ/
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