ERP, BI, and Financial Reporting

🏢 ERP, BI & Financial Reporting – Full Course Track

Welcome to the QuantML track on ERP integration, BI automation, and report generation — the place where enterprise data stops being a monster and starts becoming fuel for your dashboards, reports, and automations.

This is for finance professionals, EPM consultants, and BI wizards who want to connect Python with enterprise systems, clean up ugly export files, and generate accurate, automated reports — with commentary, charts, and yes, even PowerPoint slides if you really insist.

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🧠 What You’ll Learn

You’ll go from:

“I have three Excel exports from Oracle with 1,500 rows each…”
to
“Here’s a single cleaned dataset powering my dashboard, report deck, and GPT commentary engine.”

You’ll learn how to:

• Automate data ingestion from ERP + BI tools

• Clean, consolidate, and reconcile data with Python

• Generate financial reporting packages programmatically

• Use GPT to explain reports, generate insights, and prep decks

• Build real dashboards from real ERP messes

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🧱 How This Track Works

Each module comes with:

• ✅ Live Python notebooks

• 📁 Sample ERP exports (Oracle, SAP, NetSuite)

• 📊 BI reports in Excel / CSV formats

• 📄 Real-world financial reporting templates

• 🧰 Reusable automation tools

No fake datasets. No “perfect” demo data. Only enterprise-grade chaos — tamed.

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🔥 Complete Module Breakdown

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✅ Module 0 – Working with ERP + BI Exports

Goal: Understand common data structures, formats, and pain points
Outcome: You’ll stop crying at pivot tables

Lessons:

• Common export types: GL detail, trial balance, budget dump, transactional data

• Parsing Workday/SAP/Oracle/Netsuite exports in Python

• Understanding BI tool output (Power BI, Tableau, Qlik)

• Tips for standardizing BU, GL, and account mappings

• Building a raw → clean data pipeline

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✅ Module 1 – Data Consolidation & Reconciliation

Goal: Merge multiple sources into one trusted dataset
Outcome: Your team stops emailing you asking “which version to use?”

Lessons:

• Merging actuals, budget, forecast, PY into one dataset

• Reconciliation logic: variance checks, totals matching, duplicates

• Python scripts for multi-company, multi-entity consolidation

• Alerts for mismatches or reconciliation errors

• Generating standardized trial balances

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✅ Module 2 – Automated Financial Statements

Goal: Build income statement, balance sheet, and cash flow reports programmatically
Outcome: You’ll build reporting tools instead of formatting tables for 3 hours

Lessons:

• Creating P&L structures using mapping tables

• Grouping accounts into standardized formats

• Automating subtotals, sign reversals (because liabilities are weird)

• Outputting clean, formatted Excel reports

• Embedding variance logic for review-ready statements

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✅ Module 3 – Power BI + Tableau + Excel Integration

Goal: Push cleaned data into reporting tools (without crying)
Outcome: Your BI dashboards actually work the way they're supposed to

Lessons:

• Exporting Python output into Excel for BI tools

• Writing data to .csv/.xlsx for Power BI refresh

• Triggering Tableau data source updates via Python

• Folder structure automation: daily refresh pipelines

• GPT commentary fields for embedding inside dashboards

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✅ Module 4 – Reporting Packages & Deck Generation

Goal: Automate your board packs and internal reports
Outcome: One click → PowerPoint → CEO happy

Lessons:

• Building full reporting packs with python-pptx

• Auto-filling charts, tables, titles

• GPT-generated management commentary

• Packaging with email-ready PDF exports

• Scheduled runs + outputs for monthly review

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✅ Module 5 – GPT-Enhanced BI Reporting

Goal: Combine LLMs with your ERP/BI outputs
Outcome: Your dashboards talk back

Lessons:

• Extracting key trends from ERP reports

• GPT prompts for “explain this chart”

• Writing GPT summaries per business unit / metric

• Creating “Smart Commentary” zones in Power BI/Tableau

• Automating insight generation for leadership reporting

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✅ Module 6 – Real-World Reporting Apps

Goal: Build apps your team can use, not just code
Outcome: You become the IT department (but cooler)

Projects:

• Streamlit-based Financial Reporting Portal

• Excel Export Bot with GPT Notes

• ERP Dump → Clean P&L Builder

• Commentary-Ready BI Dataset Generator

• Monthly Reporting Assistant (reads, summarizes, emails)

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🎯 Who This Is For

This track is made for:

• EPM & ERP consultants

• FP&A teams dealing with Oracle, SAP, NetSuite

• BI analysts trying to avoid Power Query for the 12th time

• Finance folks dealing with “reports” that come in 14 tabs and require a prayer to open

• Anyone who wants to build a real pipeline from ERP → Report → Deck

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🧠 Tools You’ll Use

• Python (pandas, openpyxl, python-pptx, pyodbc)

• Excel, Power BI, Tableau

• GPT/OpenAI for insights

• Streamlit for dashboarding

• Cron jobs / Task Scheduler for automation (advanced)

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👇 Get Started

ERP pain is universal. Automating it shouldn’t be a mystery.

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