- Lab
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Libraries: If you want this lab, consider one of these libraries.
- Cloud
- Data
Analyze Web Traffic in Time Series Data with Kusto Query Language (KQL)
In this hands-on lab, you will use Kusto Query Language (KQL) in Azure to analyze website traffic data and identify unusual visitor activity. You will aggregate traffic into different time intervals, visualize trends, and compare visitor patterns across traffic sources. You will also use advanced time series functions to handle missing data, identify recurring patterns, and detect anomalies that may indicate unexpected spikes or drops in website traffic.
Lab Info
Table of Contents
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Challenge
Analyze Website Traffic Trends Using Time Binning and Aggregation
In this objective, you will use KQL aggregation functions to analyze website traffic across different time intervals. You will group visitor counts into hourly and daily intervals, compare traffic patterns across sources, and visualize trends using timecharts.
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Challenge
Construct and Analyze Structured Website Traffic Time Series
In this objective, you will use KQL time series functions to transform website traffic records into structured time series. You will create and compare multiple series, identify missing observations, and apply techniques to fill gaps in the data.
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Challenge
Identify Seasonal Traffic Patterns and Detect Anomalies
In this objective, you will analyze website traffic to identify recurring patterns, seasonal variations, and unusual activity. You will use KQL functions to separate trends from expected traffic behavior and detect anomalies such as unexpected spikes or drops in visitor counts.
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