Arpit Agrawal

Arpit Agrawal

Data Analyst · Microsoft

Data Analyst · Data Engineer · Visual Storyteller

Currently: Analytics (Vendor) at Microsoft · Building data products with SQL, Python & Power BI.

Resume
Overview · Retail & Ops Analytics
Snapshot: I build analytics systems that cut reporting time, stabilise ops, and make promotions accountable.
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End-to-end analytics projects
SQL · Python · BI
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Reporting efficiency uplift
Automation focus
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Domains: retail, ops, supply, print
Cross-industry

Short demo of the Retail & Logistics Intelligence Hub.

Retail & Logistics — walkthrough

End-to-end analytics hub for routing optimisation, forecasting, and operations insights.

Built using: SQL · Power BI · Azure · Python
Inspired by internal Microsoft reporting patterns (demo only).

Skills & Experience

Interactive skill map — click a node to filter projects. Drag to pan.

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Selected skill: Click a node to see details.
Work · Project Gallery

Use search, personas, or tags to explore case studies.

Systems & Playbooks

Reusable analytics systems I keep reaching for.

Playbook

Promotion Profitability Engine

End-to-end framework that combines promo flags, uplift modelling, and margin tracking to answer “Did this promotion actually pay off?” in one place.
Inputs: POS + campaign data · Outputs: ROI view, cannibalisation risk · Stack: Python, SQL, Power BI
System

Logistics Ops Healthboard

Route performance, SLAs, and exception management in a single hub designed around ops stand-ups, not just pretty charts.
Inputs: telemetry, order logs · Outputs: daily health score · Stack: Snowflake, SQL, Tableau
Playbook

Anomaly Radar for Supply Events

Streaming anomaly detection pipeline with clear thresholds, alerting rules, and dashboards that separate “noise” from “drop everything” events.
Inputs: event streams · Outputs: alert feed + triage board · Stack: Spark, Azure, Power BI
About · How I Work

Working principles

A few rules I use to keep analytics useful, not just “interesting”.

Make it measurable
Every dashboard must answer a decision question and have an owner. No orphan visuals.
Design for the meeting
I design views for weekly stand-ups and monthly reviews, not vague “exploration”.
Automate the boring
Manual Excel steps are red flags. If it repeats, it gets scripted or modelled.
Stay explainable
Models are only as good as the story stakeholders can tell with them in 2 minutes.

Timeline & credentials

  • 2025 — Present · Data Analyst (Vendor) at Microsoft via BlitzPath Innovation.
  • 2023 — 2024 · Data Analyst at ESVADHYAYA & consulting projects.
  • Before · Analytics across education, manufacturing, and ops.
Selected certifications
Machine Learning with Python — freeCodeCamp
Google Analytics (GA4) — Google Skillshop
SQL (Intermediate) — HackerRank
Programming Foundations with Python — CodeSignal / HackerRank
Notes from the field
I’m currently exploring how to bring promotion analytics, supply chain anomaly detection, and geospatial delivery insights into one “ops command center” — with real-time-ish data and less slideware.
Contact

Shoot a short note — demo submit only (replace with webhook in JS).