Learning Splunk - Reporting Log Data – Tables

This video tutorial covers how to use tables to represent data in Splunk, explore advanced visualizations, and utilize search commands. It includes a practical example using AWS instance data to create reports and dashboards. The tutorial guides viewers through building tables in Splunk, extracting fields, and saving searches as reports.

What is one of the main benefits of using tables to represent data in Splunk?

• They provide a visual representation of data trends.

• They automatically generate alerts for data anomalies.

• They allow for complex mathematical calculations.

• They present data in a more meaningful format, similar to a spreadsheet.

In the context of Splunk, what is a key advantage of using tables over graphs?

• Tables are more visually appealing.

• Tables can display actual data values directly.

• Tables require less processing power.

• Tables can automatically update in real-time.

What type of data is used in the example scenario involving AWS instances?

• Social media data

• Weather data

• Financial transaction data

• Network log data

What is the purpose of changing the time range in a Splunk search?

• To adjust the visualization style

• To increase the search speed

• To filter data by specific users

• To focus on events within a certain timeframe

Which field is NOT typically included when building a table to report login attempts in Splunk?

• User's email address

• Action (success or failure)

• Time of the event

• Source IP address

What is the final step after building a table in Splunk to report login attempts?

• Exporting the table to a CSV file

• Deleting the search history

• Saving the search as a report

• Sharing the table with other users

What command is used to create a table in Splunk?

• chart

• table

• eval

• stats