Dashboard consolidation for operations KPIs

Purpose

1. Automate the aggregation, visualization, and reporting of operations KPIs (such as punctuality, delays, train utilization, incidents) across multiple business tools and data sources for all metro lines, with secure access controls and cross-departmental workflows.

2. Automate daily, weekly, and real-time updates for executive monitoring, service performance analysis, compliance oversight, and operational decision-making.

3. Automating manual data collection, reducing human error, and enabling automated alerts for deviations to streamline operations management and compliance audits.

Trigger Conditions

1. Automate based on scheduled intervals (hourly, daily, weekly).

2. Trigger automation on data update in source systems (e.g., database changes, API webhook events).

3. Automator starts on manual command if urgent review required.

4. Automate exceptions, such as SLA breaches or data integrity failures.

5. New incident or operations report submission automates data fetch and dashboard refresh.

Platform Variants

1. Microsoft Power BI

• Feature/Setting: Use REST API to automate data set refresh and embed dashboard URLs; configure gateway for automating on-premises source sync.
  

2. Tableau

• Feature/Setting: Automate data source refresh via Tableau Extract API; set up schedule in Tableau Server/Online for automating visual updates.
  

3. Google Data Studio

• Feature/Setting: Automate integration via Google Sheets API and BigQuery connectors; automate scheduled refresh.
  

4. Looker

• Feature/Setting: Automate queries using Looker API; schedule report automations for critical KPIs.
  

5. Salesforce

• Feature/Setting: Report and Dashboard API to automate pulling operational performance data for automating embedded metro KPIs.
  

6. Snowflake

• Feature/Setting: Automate scheduled data warehouse sync with external metro operations data via Snowflake’s Task and Streams API.
  

7. AWS QuickSight

• Feature/Setting: Automate data ingestion through AWS SDK; automate reports for operations KPIs.
  

8. Datadog

• Feature/Setting: Dashboard API to automate custom metrics and operational alerts for train performance.
  

9. Splunk

• Feature/Setting: Automate collection of incident logs via HTTP Event Collector; setup scheduled dashboard refresh automation.
  

10. Google BigQuery

• Feature/Setting: Automate SQL views for operations KPIs; trigger automations on schedule using Cloud Functions.
  

11. IBM Cognos Analytics

• Feature/Setting: Schedule automated reports and dashboard auto-refresh for service performance metrics.
  

12. SAP Analytics Cloud

• Feature/Setting: Automate data refresh through live data connections and schedule KPI dashboard automation.
  

13. Jira

• Feature/Setting: Automate ticket-to-KPI pipeline through REST API; trigger updates to ops dashboard on incident status change.
  

14. ServiceNow

• Feature/Setting: Automate delivery of incident management metrics to custom dashboards via scripted REST API.
  

15. Monday.com

• Feature/Setting: Public API to automate board data extraction and automate real-time update of KPI widgets.
  

16. Smartsheet

• Feature/Setting: Use Sheet and Report API to automate pulling operational stats for dashboard visualization.
  

17. Notion

• Feature/Setting: Automate page database queries for incidents and automate statistics embedding with Notion API.
  

18. Asana

• Feature/Setting: Automate retrieval of task compliance rates; push automated summaries to central dashboard.
  

19. Google Sheets

• Feature/Setting: Automate data sync with metro operational systems using Apps Script triggers for dashboard updates.
  

20. Power Automate

• Feature/Setting: Automate data transfers, kicks off dashboard refresh flow via connectors (Power BI, SQL, Google Sheets).
  

21. Oracle Analytics Cloud

• Feature/Setting: Automate scheduled refresh of KPI reports; configure notification automator for exceptions.
  

Benefits

1. Accelerates operational reporting, automating aggregation, and reduces manual effort across teams.

2. Automates exception detection, enabling proactive management with minimal latency.

3. Automated dashboards improve compliance, audit trails, and executive visibility.

4. Automates data pipeline integrity monitoring, minimizing operational risks.

5. Enables scalable automating as data volume, lines, and performance KPIs expand.