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Version: Atlas 2022.3.2

Data Utilization Overview


Data Utilization

The Atlas Data Utilization Application provides Splunk administrators with comprehensive insights about who is your using your Splunk data and how.

Data Utilization includes a Key Metrics panel with KPIs that provide a quick summary of overall dataset and license utilization. An Utilization Overview panel lists ALL your datasets by Index:SourceType/Source and their utilization in descending order for at-a-glance identification of datasets that warrant more scrutiny. Clicking on one of these datasets populates Investigation panels with query history, users, and the fields contained in that dataset - this additional detail allows a rapid assessment of what business value that dataset may provide and how it is currently being utilized.

The information provided by the Data Utilization element is absolutely crucial for supporting resource optimization efforts, implementing data hygiene best practices in your Splunk environment, and helping to ensure you're getting the best utilization and the most value from your business data. Some underutilized and unneeded datasets may be deprecated to save storage and license costs; others may deserve more attention to extract valuable insights - Data Utilization provides powerful leverage for both scenarios.

Data Utilization Capabilities

  • Analyzes Index and Source Type utilization across ad-hoc searches, scheduled searches, and dashboards

  • Provides key metrics that identify underutilized datasets counts along with volume and percentage of license under-utilization

  • Provides a comprehensive list of all datasets by index:sourcetype or index:sourcetype:source and their utilization by ad-hoc and scheduled searches and dashboards

  • Provides query counts, license usage, and queries/GB distribution metrics by dataset in tabular and visual formats

  • Identifies which users, searches, and dashboards are utilizing selected datasets, and which Splunk app is hosting each search

  • Review all of the searches and the SPL being run against selected datasets

  • Easily identify inefficient searches that are using wildcards too broadly

  • Provides a comprehensive view of dataset utilization details in one pane of glass