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Z -Score and outliers : when statistics meet telemetry

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#telemetry

Dynamics 365 ERP - Development

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Dec 25, 2024

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  • The article discusses the importance of detecting outliers in data analysis, particularly in the context of telemetry and statistics.
  • The author uses the analogy of babies of varying heights to explain how outliers can skew average values and distort the understanding of a dataset.
  • The concept of Z-score is introduced as a statistical tool to identify outliers in a population distribution.
  • The author provides a step-by-step guide on how to calculate and interpret Z-scores in a given dataset using Kusto Query Language (KQL).
  • The importance of removing outliers from data analysis to obtain a more accurate representation of the population is emphasized.
  • The article concludes with a reminder that outliers need to be carefully analyzed and understood, as they may indicate underlying issues that require further investigation.
  • The author wishes readers a Merry Christmas and hints at further exploration of outlier analysis in the future.
  • The article also includes a playful mention of generating a Christmas tree using a KQL query, adding a light-hearted touch to the technical content.

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