Cena školení je 4 000 EUR a bude přepočtena aktuálním kurzem v poslední den školení.

This course is for Splunk Power Users who want to become experts on the following Splunk topics : Working with Time :for power
users who want to become experts at using time in searches. Topics will focus on searching and formatting time in addition to using
time commands and working with time zones. Statistical Processing :to identify and use transforming commands and eval
functions to calculate statistics on their data. Topics will cover data series types, primary transforming commands, mathematical and
statistical eval functions, using eval as a function, and the rename and sort commands. Comparing Values :to learn how to compare
field values using eval functions and eval expressions. Topics will focus on using the comparison and conditional functions of the
eval command, and using eval expressions with the field format and where commands Result Modification :to use commands to
manipulate output and normalize data. Topics will focus on specific commands for manipulating fields and field values, modifying
result sets, and managing missing data. Additionally, students will learn how to use specific eval command functions to normalize
fields and field values across multiple data sources. Correlation Analysis :to learn how to calculate co-occurrence between fields
and analyze data from multiple datasets. Topics will focus on the transaction, append, appendcols, union, and join commands.
Creating Knowledge Objects :to learn how to create knowledge objects for their search environment using the Splunk web
interface. Topics will cover types of knowledge objects, the search-time operation sequence, and the processes for creating event
types, workflow actions, tags, aliases, search macros, and calculated fields. Creating Field Extractions :to learn about field
extraction and the Field Extractor (FX) utility. Topics will cover when certain fields are extracted and how to use the FX to create
regex and delimited field extractions. Data Models :to learn how to create and accelerate data models. Topics will cover datasets,
designing data models, using the Pivot editor, and accelerating data models.

Working with Time

Statistical Processing

Comparing Values

Result Modification

Correlation Analysis

Creating Knowledge Objects

Creating Field Extractions

Data Models

To be successful, students should have a solid understanding of the
following:

How Splunk works
Creating search queries
Prerequisites can be obtain with free elearning :

What is Splunk (SSC)　: https://www.splunk.com/en_us/training/courses/what-is-splunk.html

Intro to Splunk (SSC)　: https://www.splunk.com/en_us/training/courses/intro-to-splunk.html

Using Fields (SSC)　: https://www.splunk.com/en_us/training/courses/using-fields.html

Visualizations (SSC)　: https://www.splunk.com/en_us/training/courses/visualizations.html

Intro to Knowledge Objects (SSC) : https://www.splunk.com/en_us/training/courses/intro-to-knowledge-objects.html

Search Under the Hood (SSC) : https://www.splunk.com/en_us/training/courses/search-under-the-hood.html

Or ask Arrow Education Team for Prerequisites Fast Start bundle (SPL_PREREQ)

Working with Time :

Module 1 - Searching with Time

Understand the _time field and timestamps
View and interact with the Event Timeline
Use the earliest and latest time modifiers
Use the bin command with the _time field
　

Module 2 - Formatting TIme

Use various date and time eval functions to format time
　

Module 3 - Using Time Commands

Use the timechart command
Use the timewrap command
　

Module 4 - Working with Time Zones

Understand how time and timezones are represented in your data
Determine the time zone of your server
Use strftime to correct timezones in results
Statistical Processing :

Module 1 - What is a Data Series

Introduce data series
Explore the difference between single-series, multi-series, and time series data series
　

Module 2 - Transforming Data

Use the chart, timechart, top, rare, and stats commands to transform events into data tables
　

Module 3 - Manipulating Data with eval Command

Understand dthe eval command
Explore and perform calculations using mathematical and statistical eval functions
Perform calculations and concatenations on field values
Use the eval command as a function with the stats command
　

Module 4 - Formatting Data

Use the rename command
Use the sort command
Comparing Values

Module 1 - Using eval to Compare

Understand the eval command
Explain evaluation functions
Identify and use comparison and conditional functions
Use the fieldformat command to format field values
　

Module 2 - Filtering with where

Use the where command to filter results
Use wildcards with the where command
Filter fields with the information functions, isnull and isnotnull
Result Modification

Module 1 -　Manipulating Output

Convert a 2-D table into a flat table with the untable command
Convert a flat table into a 2-D table with the xyseries command
　

Module 2 -　Modifying Result Sets

Append data to search results with the appendpipe command
Calculate event statistics with the eventstats command
Calculate "streaming" statistics with the streamstats command
Modify values to segregate events with the bin command
　

Module 3 -　Managing Missing Data

Find missing and null values with the fillnull command
　

Module 4 -　Modifying Field Values

Understand the eval command
Use conversion and text eval functions to modify field values
Reformat fields with the foreach command
　

Module 5 -　Normalizing with eval

Normalize data with eval functions
Identify eval functions to use for data and field normalization
Correlation Analysis　

Module 1 -　Calculate Co-Occurrence Between Fields

Understand transactions
Explore the transaction command
　

Module 2 -　Analyze Multiple Data Sources

Understand subsearch
Use the append, appendcols, union, and join commands to combine, analyze, and compare multiple data sources
Creating Knowledge Objects

Topic 1 –　Knowledge Objects & Search-time Operations

Understand role of knowledge objects for enriching data
Define search-time operation sequence
　

Topic 2 – Creating Event Types

Define event types
Create event types using three methods
Tag event types
Compare event types and reports
Topic 3 – Creating Workflow Actions

Identify what are workflow actions
Create a GET, POST, and search workflow action
Test workflow actions
　

Topic 4 – Creating Tags and Aliases

Describe field aliases and tags
Create field aliases and tags
▪ Search with field aliases and tags
　

Topic 5 – Creating Search Macros

Explain search macros
Create macros with and without arguments
Validate macro arguments
Use and preview macros at search time
Create and use nested macros
Use macros with other knowledge objects
　

Topic 6 – Creating Calculated Fields

Explain calculated fields
Create a calculated field
Use a calculated field in search
Creating Field Extractions

Module 1 - Using the Field Extractor

Understand types of extracted fields and when they are extracted
Explore the Splunk Web Field Extractor (FX)
　

Module 2 -　Creating Regex Field Extractions

Identify basics of regular expressions (regex)
Understand the regex field extraction workflow
Edit regex for field extractions
　

Module 3 -　Creating Delimited Field Extractions

Identify delimited field values in event data
Understand the delimited field extraction workflow
Data Models

Module 1 - Introducing Data Model Datasets

Understand data models
Add event, search, and transaction datasets to data models
Identify event object hierarchy and constraints
Add fields based on eval expressions to transaction datasets
　

Module 2 - Designing Data Models

Create a data model
Add root and child datasets to a data model
Add fields to data models
Test a data model
Define permissions for a data model
Upload/download a data model for backup and sharing
　

Module 3 - Creating a Pivot

Identify benefits of using Pivot
Create and configure a Pivot
Visualize a Pivot
Save a Pivot
Use Instant Pivot
Access underlying search for Pivot
　

Module 4 - Accelerating Data Models

Understand the difference between ad-hoc and persistent data model acceleration
Accelerate a data model
Describe the role of tsidx files in data model acceleration
Review considerations about data model acceleration

Certification : Splunk Core Certified Power User