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| Section | Weight | Objectives |
|---|---|---|
| Using the Common Information Model (CIM) Add-On | 5% | - Use CIM to standardize data across sources - Describe Splunk CIM purpose and structure - Normalize data using CIM knowledge objects |
| Creating and Using Field Aliases and Calculated Fields | 10% | - Define and use field aliases - Create calculated fields with eval - Manage field extractions and aliases |
| Creating Data Models | 10% | - Define data model objects and attributes - Understand data models and Pivot - Create and use data models |
| Creating and Using Workflow Actions | 10% | - Describe GET, POST, and Search workflow actions - Create and configure workflow actions - Use workflow actions to extend searches |
| Correlating Events | 15% | - Group events by fields and time - Compare transactions vs stats commands - Identify and use transactions |
| Creating Tags and Event Types | 10% | - Create and apply tags to fields or values - Use tags and event types in searches - Define event types to categorize events |
| Filtering and Formatting Results | 15% | - Sort, rename, and limit results - Use fillnull, eval, and other formatting commands - Use search and where commands |
| Using Macros | 10% | - Add and use arguments in macros - Create and reuse search macros - Manage macro permissions and sharing |
| Transforming Commands and Visualizations | 15% | - Format results for presentation - Create and customize visualizations - Use transforming commands to structure data |
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NEW QUESTION # 236
A user runs the following search:
index-X sourcetype=Y I chart count (domain) as count, sum (price) as sum by product, action usenull=f useother-f Which of the following table headers match the order this command creates?
Answer: A
Explanation:
The correct answer is C. Product, count: addtocart, count: remove, count: purchase, sum: addtocart, sum:
remove, sum: purchase1.
In Splunk, the chart command is used to create a table or a chart visualization from your data2. The chart command takes at least one function and one field, and optionally another field to group by2.
In the given search, the chart command is used with two functions (count and sum), two fields (domain and price), and two fields to group by (product and action). The usenull=f and useother=f options are used to exclude null values and other values from the chart2.
The chart command creates a table with headers that match the order of the fields and functions in the command1. The headers for the count function are prefixed with count:, and the headers for the sum function are prefixed with sum:1. The values of the product and action fields are used as the suffixes for the headers1.
Therefore, the table headers created by this command are Product, count: addtocart, count: remove, count:
purchase, sum: addtocart, sum: remove, and sum: purchase1.
NEW QUESTION # 237
What are the two parts of a root event dataset?
Answer: A
Explanation:
Reference:https://docs.splunk.com/Documentation/SplunkLight/7.3.5/GettingStarted/Designdatamodelobjects
NEW QUESTION # 238
Data model fields can be added using the Auto-Extracted method. Which of the following statements describe Auto-Extracted fields? (select all that apply)
Answer: A,B,C,D
Explanation:
Data model fields are fields that describe the attributes of a dataset in a data model2. Data model fields can be added using various methods such as Auto-Extracted, Evaluated or Lookup2. Auto-Extracted fields are fields that are automatically extracted from your raw data using various techniques such as regular expressions, delimiters or key-value pairs2. Auto-Extracted fields can be hidden in Pivot, which means that you can choose whether to display them or not in the Pivot interface2. Therefore, option A is correct. Auto-Extracted fields can have their data type changed, which means that you can specify whether they are strings, numbers, booleans or timestamps2. Therefore, option B is correct. Auto-Extracted fields can be given a friendly name for use in Pivot, which means that you can assign an alternative name to them that is more descriptive or user-friendly than the original field name2. Therefore, option C is correct. Auto-Extracted fields can be added if they already exist in the dataset with constraints, which means that you can include them in your data model even if they are already extracted from your raw data by applying filters or constraints to limit the scope of your dataset2. Therefore, option D is correct.
NEW QUESTION # 239
The Field Extractor (FX) is used to extract a custom field. A report can be created using this custom field. The created report can then be shared with other people in the organization. If another person in the organization runs the shared report and no results are returned, why might this be? (select all that apply)
Answer: A,C
Explanation:
The Field Extractor (FX) is a tool that helps you extract fields from your events using a graphical interface2. You can create a report using a custom field extracted by the FX and share it with other users in your organization2. However, if another user runs the shared report and no results are returned, there could be two possible reasons. One reason is that the extraction is private, which means that only you can see and use the extracted field2. To make the extraction available to other users, you need to make it global or app-level2.
Therefore, option C is correct. Another reason is that the other user does not have access to the index where the events are stored2. To fix this issue, you need to grant the appropriate permissions to the other user for the index2. Therefore, option D is correct. Options A and B are incorrect because they are not related to the field extraction or the report.
NEW QUESTION # 240
Which of the following knowledge objects can reference field aliases?
Answer: D
Explanation:
Field aliases in Splunk are alternate names assigned to fields. These can be particularly useful for normalizing data from different sources or simply for making field names more intuitive. Once an alias is created for a field, it can be used across various Splunk knowledge objects, enhancing their flexibility and utility.
A: Calculated fields, lookups, event types, and tags: This is the correct answer. Field aliases can indeed be referenced in calculated fields, lookups, event types, and tags within Splunk. When you create an alias for a field, that alias can then be used in these knowledge objects just like any standard field name.
* Calculated fields: These are expressions that can create new field values based on existing data. You can use an alias in a calculated field expression to refer to the original field.
* Lookups: These are used to enrich your event data by referencing external data sources. If you've created an alias for a field that matches a field in your lookup table, you can use that alias in your lookup configurations.
* Event types: These are classifications for events that meet certain search criteria. You can use field aliases in the search criteria for defining an event type.
* Tags: These allow you to assign meaningful labels to data, making it easier to search and report on. You can use field aliases in the search criteria that you tag.
NEW QUESTION # 241
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