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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Filtering and Formatting Results | 15% | - Use fillnull, eval, and other formatting commands - Use search and where commands - Sort, rename, and limit results |
| Topic 2: Creating and Using Field Aliases and Calculated Fields | 10% | - Manage field extractions and aliases - Create calculated fields with eval - Define and use field aliases |
| Topic 3: Correlating Events | 15% | - Compare transactions vs stats commands - Group events by fields and time - Identify and use transactions |
| Topic 4: Creating Data Models | 10% | - Define data model objects and attributes - Understand data models and Pivot - Create and use data models |
| Topic 5: Creating and Using Workflow Actions | 10% | - Use workflow actions to extend searches - Create and configure workflow actions - Describe GET, POST, and Search workflow actions |
| Topic 6: Using the Common Information Model (CIM) Add-On | 5% | - Describe Splunk CIM purpose and structure - Normalize data using CIM knowledge objects - Use CIM to standardize data across sources |
| Topic 7: Creating Tags and Event Types | 10% | - Create and apply tags to fields or values - Define event types to categorize events - Use tags and event types in searches |
| Topic 8: Transforming Commands and Visualizations | 15% | - Use transforming commands to structure data - Format results for presentation - Create and customize visualizations |
| Topic 9: Using Macros | 10% | - Add and use arguments in macros - Create and reuse search macros - Manage macro permissions and sharing |
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NEW QUESTION # 203
Data model are composed of one or more of which of the following datasets? (select all that apply.)
Answer: A,B,D
Explanation:
Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/Aboutdatamodels Data models are collections of datasets that represent your data in a structured and hierarchical way. Data models define how your data is organized into objects and fields. Data models can be composed of one or more of the following datasets:
Events datasets: These are the base datasets that represent raw events in Splunk. Events datasets can be filtered by constraints, such as search terms, sourcetypes, indexes, etc.
Search datasets: These are derived datasets that represent the results of a search on events or other datasets.
Search datasets can use any search command, such as stats, eval, rex, etc., to transform the data.
Transaction datasets: These are derived datasets that represent groups of events that are related by fields, time, or both. Transaction datasets can use the transaction command or event types with transactiontype=true to create transactions.
NEW QUESTION # 204
Data model are composed of one or more of which of the fo-owing datasets? (select all that apply.)
Answer: A,B,D
Explanation:
Reference:https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/Aboutdatamodels
NEW QUESTION # 205
When using the Field Extractor (FX), which of the following delimiters will work? (select all that apply)
Answer: B,C,D
Explanation:
Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/FXSelectMethodstep
https://community.splunk.com/t5/Splunk-Search/Field-Extraction-Separate-on-Colon/m-p/29751 The Field Extractor (FX) is a tool that helps you extract fields from your data using delimiters or regular expressions. Delimiters are characters or strings that separate fields in your data. Some of the delimiters that will work with FX are:
Tabs: horizontal spaces that align text in columns.
Pipes: vertical bars that often indicate logical OR operations.
Spaces: blank characters that separate words or symbols.
Therefore, the delimiters A, B, and D will work with FX.
NEW QUESTION # 206
Which of the following statements describes field aliases?
Answer: B
Explanation:
Explanation
Field aliases are alternative names for fields in Splunk. Field aliases can be used to normalize data across different sources and sourcetypes that have different field names for the same concept. For example, you can create a field alias for src_ip that maps to clientip, source_address, or any other field name that represents the source IP address in different sourcetypes. Field aliases can also be used in lookup file definitions to map fields in your data to fields in the lookup file. For example, you can use a field alias for src_ip to map it to ip_address in a lookup file that contains geolocation information for IP addresses. Field alias names do not replace the original field name, but rather create a copy of the field with a different name. Field alias names are case sensitive when used as part of a search, meaning that src_ip and SRC_IP are different fields.
NEW QUESTION # 207
When would transaction be used instead of stats?
Answer: C
Explanation:
The transaction command is used to group events that are related by some common fields or conditions, such as start/end values, time span, or pauses. The stats command is used to calculate statistics on a group of events by a common field value.
Reference
Splunk Community
Splunk Transaction - Exact Details You Need
NEW QUESTION # 208
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