Academic Operations & Lesson ManagementPurpose
1.2. Deliver automated dashboards and reports to academic staff, leadership, and parents to ensure continuous insight into performance metrics, attendance correlations, subject-wise trends, and cohort analytics for comprehensive secondary schools.
Trigger Conditions
2.2. Data update events: new grade entries, exam results uploads, or attendance changes in school management systems.
2.3. Manual initiation by educators via a single-click interface or request form submission.
Platform Variants
• Feature/Setting: Automate dashboard refresh on dataset update via REST API; configure refresh schedule in Power BI Service.
3.2. Google Sheets
• Feature/Setting: Automate import and analysis using Google Apps Script triggers and Sheets API; scheduled scripts to analyze grades.
3.3. Microsoft Excel Online
• Feature/Setting: Automate data fetch with Power Automate flows; configure Excel Online (Business) connector to update and analyze datasets.
3.4. Tableau
• Feature/Setting: Automate data pipeline using Tableau Prep Conductor; schedule automatic run and extract refresh via Tableau Server REST API.
3.5. Salesforce Education Cloud
• Feature/Setting: Automate analytics with Einstein Analytics; configure scheduled dataflows and real-time alerts for trends.
3.6. AWS Lambda
• Feature/Setting: Automate data aggregation/transformation using Python scripts; trigger via CloudWatch on S3 data update.
3.7. Zapier
• Feature/Setting: Automate workflows connecting CRM, SMS, and sheet systems; configure Zaps to integrate and analyze student records.
3.8. Google Data Studio
• Feature/Setting: Automate report updates on data source change; schedule email delivery of dashboards.
3.9. SIS (Student Information System) APIs (e.g., PowerSchool, Arbor)
• Feature/Setting: Automate grade data extraction via REST API endpoints; configure custom webhooks for real-time sync.
3.10. Slack
• Feature/Setting: Automate report delivery to channels via Incoming Webhooks; configure alarms for outlier trends.
3.11. Microsoft Teams
• Feature/Setting: Automate scheduled posting of trend highlights using Teams connector in automation flows.
3.12. Alteryx
• Feature/Setting: Automate workflow jobs using Alteryx Server and Scheduler to update analysis datasets.
3.13. Python (Pandas library)
• Feature/Setting: Automate batch analysis of CSV/Excel files; schedule with cron jobs.
3.14. Google Classroom API
• Feature/Setting: Automate extraction of assignment grades and progress for ingestion into reporting tools.
3.15. Azure Logic Apps
• Feature/Setting: Automate multi-step workflows to pull, transform, and push performance data; schedule recurrence.
3.16. Airflow
• Feature/Setting: Automate and orchestrate complex ETL pipelines for advanced analysis using DAGs.
3.17. IBM Cognos Analytics
• Feature/Setting: Automate report generation and delivery schedules; set triggers on data upload.
3.18. R (Shiny)
• Feature/Setting: Automate interactive web app updates with new data; schedule batch script executions for summary stats.
3.19. Looker (Google Cloud)
• Feature/Setting: Automate dashboard refresh and data modeling using LookML; configure schedule for data pull.
3.20. Trello
• Feature/Setting: Automate card creation for at-risk students with Power-Ups or Butler automation rules from analyzed data.
Benefits
4.2. Enables real-time or near-real-time automated insight into student performance, attendance, progression, and subject-level trends.
4.3. Streamlines early intervention via automating alerts and highlight mechanisms for at-risk students or declining trends.
4.4. Drives automatable curriculum improvement through automated longitudinal and comparative analysis.
4.5. Centralizes, standardizes, and archives all automated reports for compliance and ongoing reference.
4.6. Reduces analysis errors while automating complex data aggregations and trend visualizations.
4.7. Automating the process ensures scalable, repeatable, and timely dissemination of actionable intelligence to all stakeholders.