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SUMMARY:Common issues with Time Series data and how to solve them - Vadim 
 Nelidov
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DTSTAMP:20260808T191704Z
UID:pretalx-pyconde-pydata-berlin-2023-ZRAFKA@pretalx.com
DESCRIPTION:Time-series data is all around us: from logistics to digital m
 arketing\, from pricing to stock\nmarkets. It’s hard to imagine a modern
  business that has no time series data to forecast.\nHowever\, mastering s
 uch forecasting is not an easy task.\nFor this talk\, together with other 
 domain experts\, I have collected a list of common time\nseries issues tha
 t data professionals commonly run into. After this talk\, you will learn t
 o\nidentify\, understand\, and resolve such issues. This will include stab
 ilising divergent time\nseries\, organising delayed / irregular data\, han
 dling missing values without anomaly propagation\,\nand reducing the impac
 t of noise and outliers on your forecasting models.
LOCATION:B05-B06
URL:https://pretalx.com/pyconde-pydata-berlin-2023/talk/ZRAFKA/
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