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Schedules Dashboard

The Schedules Dashboard, part of Paradime's Radar suite, offers comprehensive insights into your dbt™ schedule performance. This tool enables teams to effectively monitor, optimize, and make data-driven decisions to enhance their data pipeline's efficiency and reliability.

Prerequisites

The Schedules dashboard is divided into two main sections:

  1. Overview: Provides a high-level summary of all schedules. [link]

  2. Detailed: Offers in-depth analytics for individual schedules. [link]

Overview Section

The Overview section gives you a broad perspective on your dbt™ schedules' performance, allowing you to uncover key insights, including:

1. Execution Efficiency and Reliability

Value: Quickly identify time-intensive schedules and assess overall reliability to find efficiency gains.

How to use:

  • Monitor the daily success and error rates of your dbt™ runs.

  • Investigate days with higher error rates to identify potential systemic issues.

  • Look for patterns in execution times to optimize scheduling.

  • Focus on schedules with the highest error counts for troubleshooting.

2. Resource Allocation and Performance

Value: Understand how different actors are utilizing the schedules and identify performance bottlenecks.

How to use:

  • Analyze the distribution of runs between Scheduler, Bolt Run Completed, and Manual executions.

  • Optimize automated processes if manual runs are disproportionately high.

  • Investigate and optimize schedules with consistently long runtimes.

  • Identify peak hours for schedule runs and consider load balancing if necessary.

3. Schedule Configuration and Ownership Analysis

Value: Gain insights into your current schedule configurations and ownership distribution.

How to use:

  • Review the distribution of schedule configurations.

  • Identify opportunities to consolidate or optimize cron schedules.

  • Assess the distribution of schedule ownership to ensure balanced workload across team members.

  • Consider knowledge sharing or redistribution if schedules are overly concentrated with certain owners.

4. Overall dbt™ Usage Metrics

Value: Get a quick snapshot of your dbt™ usage and performance.

How to use:

  • Track the total number of executed schedules to gauge overall dbt™ activity.

  • Monitor total execution time to assess resource usage and identify trends over time.

  • Use these metrics as high-level KPIs for your dbt™ operations.

Detailed Section

The Detailed section allows you to dive deep into individual schedule performance, providing comprehensive insights such as:

1. Schedule Reliability and Performance

Value: Analyze the consistency, reliability, and performance of individual schedules.

How to use:

  • Monitor the overall success rate and run counts to gauge schedule reliability.

  • Track the duration of each run over time to identify performance trends.

  • Investigate any patterns in errors or unusually long run times.

  • Use these metrics to prioritize which schedules need optimization or troubleshooting.

2. Model Performance and Resource Utilization

Value: Pinpoint time-consuming models and understand resource allocation within a schedule.

How to use:

  • Focus optimization efforts on the models with the highest average run times.

  • Consider refactoring or splitting large models to improve overall schedule performance.

  • Analyze the distribution of execution time across different dbt™ commands and models.

  • Identify any imbalances in resource utilization and optimize accordingly.

3. Detailed Execution Analysis

Value: Get a comprehensive view of each schedule run and individual model performance.

How to use:

  • Review the specifics of each run, including execution time, status, and runtime.

  • Analyze the performance of individual models within the schedule.

  • Use this detailed information for thorough troubleshooting and performance analysis.

  • Identify consistently problematic models or steps in your dbt™ pipeline.

4. Historical Performance Trends

Value: Understand how your schedule performance has evolved over time.

How to use:

  • Observe long-term trends in schedule execution times.

  • Identify any recurring patterns or anomalies in schedule performance.

  • Use this information to assess the impact of optimizations or changes to your dbt™ models over time.

How to Apply Filters

  1. Locate the "Select schedule" and "Select date range" dropdowns at the top of the Detailed dashboard.

  2. Choose your desired schedule and date range.

  3. The dashboard will automatically update to reflect your selections, allowing for focused analysis of specific schedules over your chosen time period.

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