Vadim Nelidov: Common issues with Time Series data and how to solve them

Time-series data is all around us: from logistics to digital marketing, from pricing to stock markets. It’s hard to imagine a modern business that has no time series data to forecast. However, mastering such forecasting is not an easy task. For this talk, together with other domain experts, I have collected a list of common time series issues that data professionals commonly run into. After this talk, you will learn to identify, understand, and resolve such issues. This will include stabilising divergent time series, organising delayed / irregular data, handling missing values without anomaly propagation,
and reducing the impact of noise and outliers on your forecasting models.