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UID:pretalx-pyconde-pydata-berlin-2023-ZRAFKA@pretalx.com
DTSTART;TZID=CET:20230417T151000
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DESCRIPTION:Time-series data is all around us: from logistics to digital ma
 rketing\, from pricing to stock\nmarkets. It’s hard to imagine a modern 
 business that has no time series data to forecast.\nHowever\, mastering su
 ch forecasting is not an easy task.\nFor this talk\, together with other d
 omain experts\, I have collected a list of common time\nseries issues that
  data professionals commonly run into. After this talk\, you will learn to
 \nidentify\, understand\, and resolve such issues. This will include stabi
 lising divergent time\nseries\, organising delayed / irregular data\, hand
 ling missing values without anomaly propagation\,\nand reducing the impact
  of noise and outliers on your forecasting models.
DTSTAMP:20260309T213828Z
LOCATION:B05-B06
SUMMARY:Common issues with Time Series data and how to solve them - Vadim N
 elidov
URL:https://pretalx.com/pyconde-pydata-berlin-2023/talk/ZRAFKA/
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