Explore Time-series Data with Kusto Query Language (KQL)

Learn to wrangle time series data with practical use cases. This course will teach you how to utilize time-series data with KQL to analyze trends, uncover patterns, and detect anomalies.
Have you ever wondered how data can predict the next big storm? Dive into real-world weather events and discover the power of KQL to reveal patterns, spot anomalies, and forecast impacts-turning raw storm data into actionable insights. In this course, Explore Time-series Data with Kusto Query Language (KQL), you'll learn how to use time-series data with KQL to analyze trends, uncover patterns, and detect anomalies. First, you'll explore how to use binning and aggregating functions along with time-series functions and visualizations to find insights from your data. Next, you'll discover how to use time-series functions like make-series and mv-expand for advanced analytics. Finally, you'll learn how to use functions like series_decompose and series_outliers to find patterns and anomalies in practical data. When you're finished with this course, you'll have the skills and knowledge of exploring time-series data with KQL needed to gain valuable insights and take intelligent actions from your data.
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