Splunk Power User Fast StartPOWER-USPSplunkSP-POWER-U10<ul>
<li>Utilize over 60 commands and functions to transform, manipulate, normalize, correlate, and filter data.</li><li>Filter data using time modifiers and time commands and use formatting functions to accommodate various time formats.</li><li>Calculate statistics using transforming commands and mathematical and statistical eval functions.</li><li>Compare, manipulate, and normalize data using several commands including the all-powerful eval command and an array of statistical, comparison, conditional, and formatting functions.</li><li>Calculate co-occurrence between fields and analyze data from multiple datasets.</li><li>Create, curate, manage and share knowledge objects.</li></ul><p>To be successful, students should have a solid understanding of the following:</p>
<ul>
<li>How Splunk works</li><li>How to create basic searching and visualizations</li></ul><ul>
<li><a class="fl-href-prod" href="/swisscom/en/course/splunk-wwt">Working with Time <span class="fl-prod-pcode">(WWT)</span></a></li><li><a class="fl-href-prod" href="/swisscom/en/course/splunk-ssp">Statistical Processing <span class="fl-prod-pcode">(SSP)</span></a></li><li><a class="fl-href-prod" href="/swisscom/en/course/splunk-scv">Comparing Values <span class="fl-prod-pcode">(SCV)</span></a></li><li><a class="fl-href-prod" href="/swisscom/en/course/splunk-srm">Result Modification <span class="fl-prod-pcode">(SRM)</span></a></li><li><a class="fl-href-prod" href="/swisscom/en/course/splunk-sclas">Correlation Analysis <span class="fl-prod-pcode">(SCLAS)</span></a></li><li><a class="fl-href-prod" href="/swisscom/en/course/splunk-cko">Creating Knowledge Objects <span class="fl-prod-pcode">(CKO)</span></a></li><li><a class="fl-href-prod" href="/swisscom/en/course/splunk-cfe">Creating Field Extractions <span class="fl-prod-pcode">(CFE)</span></a></li><li><a class="fl-href-prod" href="/swisscom/en/course/splunk-sdm">Data Models <span class="fl-prod-pcode">(SDM)</span></a></li></ul><h5>Topic 1 – Working with Time</h5><ul>
<li>Formatting Time</li><li>Comparing Index Time versus Search Time</li><li>Using Time Commands</li><li>Working with Time Zones</li></ul><h5>Topic 2 – Statistical Processing</h5><ul>
<li>What is a Data Series?</li><li>Transforming Data</li><li>Manipulating Data with eval</li><li>Formatting Data</li></ul><h5>Topic 3 – Comparing Values</h5><ul>
<li>Using eval to Compare</li><li>Filtering with where</li></ul><h5>Topic 4 – Result Modification</h5><ul>
<li>Manipulating Output</li><li>Modifying Results Sets</li><li>Managing Missing Data</li><li>Modifying Field Values</li><li>Normalizing with eval</li></ul><h5>Topic 5 – Correlation Analysis</h5><ul>
<li>Calculate Co-Occurrence Between Fields</li><li>Analyze Multiple Datasets</li></ul><h5>Topic 6 – Intro to Knowledge Objects</h5><ul>
<li>What are Knowledge Objects?</li><li>Knowledge Object Settings</li><li>Managing Knowledge Objects</li></ul><h5>Topic 7 – Creating Knowledge Objects</h5><ul>
<li>Knowledge Objects and Search-time Operations</li><li>Creating Event Types</li><li>Using Event Type Builder</li><li>Creating Workflow Actions</li><li>Creating Tags and Aliases</li><li>Creating Search Macros</li></ul><h5>Topic 8 – Creating Field Extractions</h5><ul>
<li>Using the Field Extractor</li><li>Creating Regex Field Extractions</li><li>Creating Delimited Field Extractions</li></ul><h5>Topic 9 – Data Models</h5><ul>
<li>Introducing Data Model Datasets</li><li>Designing Data Models</li><li>Creating a Pivot</li><li>Accelerating Data Models</li></ul>- Utilize over 60 commands and functions to transform, manipulate, normalize, correlate, and filter data.
- Filter data using time modifiers and time commands and use formatting functions to accommodate various time formats.
- Calculate statistics using transforming commands and mathematical and statistical eval functions.
- Compare, manipulate, and normalize data using several commands including the all-powerful eval command and an array of statistical, comparison, conditional, and formatting functions.
- Calculate co-occurrence between fields and analyze data from multiple datasets.
- Create, curate, manage and share knowledge objects.To be successful, students should have a solid understanding of the following:
- How Splunk works
- How to create basic searching and visualizations- Working with Time (WWT)
- Statistical Processing (SSP)
- Comparing Values (SCV)
- Result Modification (SRM)
- Correlation Analysis (SCLAS)
- Creating Knowledge Objects (CKO)
- Creating Field Extractions (CFE)
- Data Models (SDM)Topic 1 – Working with Time
- Formatting Time
- Comparing Index Time versus Search Time
- Using Time Commands
- Working with Time Zones
Topic 2 – Statistical Processing
- What is a Data Series?
- Transforming Data
- Manipulating Data with eval
- Formatting Data
Topic 3 – Comparing Values
- Using eval to Compare
- Filtering with where
Topic 4 – Result Modification
- Manipulating Output
- Modifying Results Sets
- Managing Missing Data
- Modifying Field Values
- Normalizing with eval
Topic 5 – Correlation Analysis
- Calculate Co-Occurrence Between Fields
- Analyze Multiple Datasets
Topic 6 – Intro to Knowledge Objects
- What are Knowledge Objects?
- Knowledge Object Settings
- Managing Knowledge Objects
Topic 7 – Creating Knowledge Objects
- Knowledge Objects and Search-time Operations
- Creating Event Types
- Using Event Type Builder
- Creating Workflow Actions
- Creating Tags and Aliases
- Creating Search Macros
Topic 8 – Creating Field Extractions
- Using the Field Extractor
- Creating Regex Field Extractions
- Creating Delimited Field Extractions
Topic 9 – Data Models
- Introducing Data Model Datasets
- Designing Data Models
- Creating a Pivot
- Accelerating Data Models4 days4000.004000.004000.004000.003335.004000.004000.004000.004000.004000.004000.004400.004000.00400.00400.00400.00400.00400.00400.00