Personal Dashboard – DS Productivity & QA Checker

Overview

The Personal Dashboard is a full analytics and QA platform I built to monitor Data Specialist (DS) work quality and productivity across large Google Sheets–based projects. It automates the entire flow: Google Sheets → Excel → SQL → DS vs QA comparison → dashboard. Instead of manually opening files and checking rows one by one, leads get a single view with KPIs, error donuts, trends, and detailed compare views for each file.

The dashboard supports both Retail and URPC domains, tracks invalid rates, and lets users drill down from high-level metrics into row-level differences between DS and QA outputs.

My Role

• Designed the end-to-end workflow around real DS/QA production bottlenecks.
• Implemented the full 3-phase pipeline: Google Sheets export, Excel normalization, and SQL ingestion.
• Built the DS vs QA comparison engines for Retail and URPC, including fingerprint logic and diff rules.
• Deployed and maintain everything on my own Linux VPS so the team can access it securely via the browser.
• Created the front-end experience with filters, charts, donut visualizations, and file-level compare views.
• Deployed and maintained everything on my own Linux VPS so the team can access it via browser.

Tech Stack

• Backend: Python, Flask blueprints, MySQL (custom schema, indexed lookups).
• Data pipeline: Google Sheets API, xlsxwriter, CSV/Excel parsing, batch exporters, log-based SQL sync.
• Frontend: HTML templates, modular CSS, custom JavaScript (filters v2, donuts, trend charts, modals).
• Analytics: SQL aggregation queries for task types, emails, daily trends, and invalid percentages.
• Infrastructure: Linux VPS (Hostinger), Nginx, Gunicorn, environment-based config.

Pipeline – From Google Sheets to Dashboard

• Phase 1 – Google Sheets → Excel: batch exporter reads a master list of task links, uses OAuth tokens per DS email, and exports each sheet as .xlsx while logging status and syncing results back to SQL.
• Phase 2 – Excel → SQL: loaders scan the exported files, normalize headers, detect DS vs QA and Retail vs URPC, and populate task tables plus dedicated header tables for later comparison.
• Phase 3 – SQL → Comparison & Analytics: compare engines align DS and QA rows via fingerprints, compute field-level mismatches, log results to SQL/CSV, and drive dashboard views, donuts, and trend charts.

Key Features

• Unified DS/QA view: central dashboard that shows all files, their status, invalid counts, task types, catalog/region, and quick actions.
• Interactive filters v2: month/week, task type, catalog, region, and email filters that update the table, donuts, and charts in sync.
• DS vs QA compare engine: Retail and URPC compare views that align rows by fingerprint and highlight field-level differences between DS and QA.
• KPI cards & donuts: top-line metrics (total files, invalid %, DS vs QA mismatch counts) and visual donut charts for quick scanning.
• Rows trend line: daily or weekly row trends across Retail and URPC, useful for tracking volume spikes and workload over time.
• File-level drilldown: clicking a row opens a detailed compare view in a new tab with sticky headers, floating scrollbar, and diff highlights.
• Log-aware exports: exporter checks both SQL and log files to avoid re-running completed jobs and to fix inconsistent statuses automatically.

Impact

Before this dashboard, leads had to manually open each DS and QA sheet, scan for invalid rows, and rely on ad-hoc filters. The Personal Dashboard turns that into a single-view system: tasks are imported automatically, compared systematically, and summarized into KPIs and charts.

In practice, it cuts review time per file from minutes to seconds for most checks, surfaces patterns in invalid fields, and makes it easy to spot which catalogs, regions, or assignees need attention. It also provides a historical view of throughput and quality, which is hard to get from raw Google Sheets alone, giving leads a reliable source of truth for performance and quality discussions.

Demo

Condensed Demo (≈1-minute overview)

Short video walkthrough of the main dashboard, filters, analytics view, and DS vs QA compare screen.

Main Dashboard View

Overview of all files with filters, KPI cards, and the main table.

Analytics & Trends

Task-type breakdowns, email summaries, and daily row trends powered by SQL aggregations.

DS vs QA Compare View

Side-by-side comparison for a single file, showing aligned DS/QA rows and highlighted field-level diffs.