Thanks to visit codestin.com
Credit goes to github.com

Skip to content
View 23-06109's full-sized avatar

Block or report 23-06109

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
23-06109/README.md

Reporting & Data Automation Specialist

Operations Analytics | BI/Data Analytics | AI-Enabled Business Operations

I'm Jimmy Jr Manalon. I turn operational data and repetitive reporting processes into reliable reporting systems, actionable insights, and automated workflows.

DATA → VISIBILITY → INSIGHT → DECISION → ACTION

My background includes operational and project reporting, KPI monitoring, data quality, process improvement, Advanced Excel automation, and cross-functional operations support. I focus on making reporting trustworthy and helping teams see what needs attention next.

Open to remote opportunities in reporting, operations analytics, BI/data analytics, and reporting automation, as well as freelance reporting and automation work. Connect with me on LinkedIn.

Selected Projects

An end-to-end Python and PostgreSQL workflow connecting ticket, agent, and QA data to SLA monitoring, team analysis, a prioritized exception register, automated Excel reporting, and a management briefing.

Evidence: 500 synthetic tickets; the saved report identifies 57 overdue open cases and 5 Critical-priority overdue cases. SQL supplies the figures; an optional, human-reviewed AI rewrite uses the prepared briefing.

View the management report · Read the briefing

Operational data → validation → KPI and risk detection → prioritized exceptions → management reporting → AI-assisted decision support.

Evidence: 300 synthetic activities; 34 Critical and 48 Warning exceptions, with a saved Excel management report, deterministic briefing, and six automated checks. The optional AI integration receives calculated evidence; the default workflow runs without an API key.

Core Analytics Project — Operations Delay & Performance Analysis

SQL and Power BI analysis of 500 simulated work orders, comparing backlog volume, overdue rates, and aging to focus management attention.

Evidence: 106 overdue open work orders at the fixed reporting date. Team-level analysis distinguishes CON-A's combined backlog risk from QA-B's small but older backlog and identifies areas for further investigation.

Supporting Projects

Project Contribution to the portfolio
Operational Reporting Automation & Business Analytics Excel Power Query cleaning and validation of 750 synthetic activities, feeding a Power BI dashboard and an overdue action list.
Project Progress KPI Dashboard Excel and Power BI reporting that turns a 20-activity tracker into planned-versus-actual progress visibility.

One Connected Reporting Story

Progression Business-value flow
Project 1 Data → KPI Visibility
Project 2 Data → Analysis → Insight
Project 3 Data → Reporting Automation → Business Analytics
Project 4 Data → Risk/Exception Detection → Decision Support → AI-Assisted Reporting
Project 5 Data → End-to-End Analytics → Decision → Automated Workflow

DATA → VISIBILITY → INSIGHT → DECISION → ACTION → MEASUREMENT

The projects demonstrate reporting outputs and evidence-based recommendations. Measuring the effect of management action is the next step in an operational deployment; these portfolio snapshots do not claim client savings or before-and-after business results.

Toolkit Demonstrated in the Repositories

  • Excel and Power Query: data preparation, validation, formulas, PivotTables, and repeatable reporting.
  • Power BI and DAX: KPI visibility, performance comparisons, and operational dashboards.
  • SQL / PostgreSQL: relational data, reusable analytical views, backlog and SLA analysis.
  • Python: data processing, exception rules, automated Excel reports, and management briefings.
  • AI-assisted reporting: evidence-grounded narrative generation and human-reviewed decision support.

My longer-term direction is Operations Analytics & AI Automation Specialist / Consultant, grounded in practical reporting and operations work.

Pinned Loading

  1. customer-support-analytics-automation customer-support-analytics-automation Public

    Flagship: Python and PostgreSQL workflow for customer-support SLA and QA analysis, prioritized exceptions, automated Excel reports, and management briefings. Synthetic data.

    Python

  2. ai-operations-reporting-assistant ai-operations-reporting-assistant Public

    Core project: Python validation, KPI monitoring, prioritized operational exceptions, and optional AI-assisted briefings, with a saved Excel management report. Synthetic data.

    Python

  3. operations-delay-performance-analysis operations-delay-performance-analysis Public

    Core analytics: PostgreSQL and Power BI analysis of 500 simulated work orders, comparing overdue rates, backlog volume, and aging to prioritize operational review.

  4. operational-reporting-automation-business-analytics operational-reporting-automation-business-analytics Public

    Excel Power Query and Power BI workflow that turns 750 synthetic activities into validated reporting data, operational KPIs, and an overdue action list.

  5. project-progress-kpi-dashboard project-progress-kpi-dashboard Public

    Excel and Power BI dashboards comparing planned versus actual progress, activity status, and discipline-level gaps across 20 synthetic project activities.