Course Outline


Review of Basic Features and Architecture of Splunk

Developing a Splunk Application and a Technology Add-on

Connecting Data to Splunk

  • Understanding various data input methods and sources
  • Processing data
  • Improving the input process

Conducting Advanced Data Analytics

  • Manipulating and filtering data
  • Combining searches and using subsearches
  • Working with time and multivalue fields
  • Creating advanced reports
  • Using geography and location
  • Using advanced transactions
  • Dealing with anomalies
  • Predicting and trending
  • Understanding machine learning

Performing Advanced Visualization

  • Drilldown
  • Sunburst Sequence
  • Geospatial visualization
  • Punchcard visualization
  • Calendar heatmap visualization
  • Sankey diagram

Customizing Dashboard

  • Using Dashboard controls
  • Managing multi-search
  • Customizing tokens
  • Customizing layout, look and feel
  • Implementing the custom alert action

Integrating Splunk with Other Enterprise Systems

  • Working with the Splunk SDK
  • Splunk with Python and R for analytics
  • Splunk with Tableau for visualization


Summary and Conclusion


  • Experience with business intelligence and data visualization
  • Knowledge of Splunk fundamentals


  • Data analysts
  • Data scientists
  • Data engineers
  14 Hours


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