High Tech — Semantic Search Model Performance Monitoring

Overview

The purpose of this DAG is to systematically monitor the performance of semantic search models within the high-tech industry. It utilizes scheduled events as triggers to initiate the workflow. The data sources include user interaction logs, model response times, and feedback surveys. The ingestion pipeline begins with the collection of performance metrics from these sources, followed by a series of processing steps that involve analyzing the performance data against predefined benchmarks. Qualit

The purpose of this DAG is to systematically monitor the performance of semantic search models within the high-tech industry. It utilizes scheduled events as triggers to initiate the workflow. The data sources include user interaction logs, model response times, and feedback surveys. The ingestion pipeline begins with the collection of performance metrics from these sources, followed by a series of processing steps that involve analyzing the performance data against predefined benchmarks. Quality controls are integrated throughout the pipeline to validate the accuracy and reliability of the data being processed. This includes checks for data completeness and consistency. The final outputs of the DAG are comprehensive performance reports and a dynamic dashboard that visualizes key performance indicators (KPIs) such as response time and user satisfaction rates. Monitoring these KPIs allows stakeholders to gain actionable insights into the effectiveness of their semantic search models. The business value of this DAG lies in its ability to enhance user experience, optimize model performance, and facilitate data-driven decision-making within the high-tech sector.

Part of the Literature Review solution for the High Tech industry.

Use cases

• Improved user satisfaction through optimized search performance
• Data-driven insights for informed decision-making
• Proactive identification of performance issues
• Enhanced reliability of semantic search models
• Streamlined reporting processes for stakeholders