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UID:pretalx-europython-2024-CMETS8@programme.europython.eu
DTSTART;TZID=CET:20240711T115500
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DESCRIPTION:In a time where GenAI is quickly growing in popularity\, along 
 with prescriptive analytics and online ML models\, the question is raised 
 whether we still need to care about data quality? We strongly believe that
  the answer is yes\, and even more so than before! \n\nOur expectations of
  data are high\, and this often leads to frustrations when reality does no
 t meet these expectations. \n\nIn the pursuit of data quality\, expectatio
 ns must be grounded in reality. It is often the case that a gap exists bet
 ween anticipated outcomes and the actual data reality\, which leads to fru
 stration and mistrust. \n\nThis talk delves into pragmatic strategies that
  can be employed to bridge this gap.  The talk  will discuss both the tech
 nical  (hard) and cultural  (soft) measures implemented to uphold these st
 andards.\n\nKey Takeaways:\n1. Integration tests serve as a proactive barr
 ier\, preempting the violation of data contracts\, unlike reactive data qu
 ality checks.\n2. Prioritisation is crucial\; a product-centric mindset is
  key when evaluating the balance between resource investment and potential
  gain.\n3. Data quality management is requiring both hard and soft measure
 s\n\n\nAre you a data scientist\, software engineer\, product manager\, or
  data engineer? Join us in this discussion\; data quality concerns us all.
DTSTAMP:20260518T123424Z
LOCATION:North Hall
SUMMARY:Don't fix bad data\, do this instead - Martina Ivanicova
URL:https://programme.europython.eu/europython-2024/talk/CMETS8/
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