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Course Outline
Introduction
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.
Troubleshooting
Summary and Conclusion
Requirements
- Experience with business intelligence and data visualization.
- Knowledge of Splunk fundamentals.
Audience
- Data analysts.
- Data scientists.
- Data engineers.
14 Hours
Testimonials (2)
The Instructor knew the information he was lecturing the class on.
Amin Muhammed - Ultimate Knowledge
Course - Advanced Splunk
Setting up the universal forwarder and heavy forwarder is something I know for a fact I will use on my team.
