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Transform and Optimize Pipelines

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How Splunk helps with this use case

Transforming and optimizing data pipelines involves re-engineering and automating the flow of data from source to destination to eliminate inefficiencies, reduce complexity, and enable real-time or near-real-time analytics. This process turns intricate, fragmented data pipelines into streamlined, manageable data engines, driving operational efficiency, lowering costs, and empowering organizations to derive greater value from their data assets. 

If this use case is new for you, we recommend reading through the following Getting Started Guide before exploring the use cases below.

Getting started with Splunk Data Management Pipeline Builders
This guide walks you through the most important high level steps, with tutorials and resources, to get started with Splunk Edge Processor and Splunk Ingest Processor.
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