Categories: Practice Datasets
Tags:

Power BI Financial Dataset by SlideScope for Data Science Projects – Structure, Meaning & Business Utility

1. Overview of the Dataset

This dataset represents a realistic, transaction-level financial extract typically used by CFOs, finance controllers, FP&A teams, and BI professionals to analyze an organization’s profitability, liquidity, and investment performance.

Get the dataset here: https://github.com/slidescope/Power-BI-Financial-Dataset-by-SlideScope-for-Data-Science-Projects

Unlike summary P&L statements, this dataset is granular, meaning:

  • Each row is a financial event
  • Revenues and expenses are recorded at operational level
  • Transactions can be aggregated dynamically in Power BI

The structure closely mirrors data pulled from:

  • ERP systems (SAP, Oracle, Tally, NetSuite)
  • Accounting software (QuickBooks, Zoho Books)
  • Financial data warehouses

This makes it ideal for executive dashboards, board reporting, and scenario analysis.

2. Dataset Granularity & Why It Matters

Each of the 300 rows represents one financial transaction, not a monthly summary.

This enables:

  • Drill-down from company-level KPIs → department → project → transaction
  • Accurate cash flow tracking
  • ROI calculation per initiative
  • Audit-friendly reporting

CFOs prefer transaction-level data because summaries hide inefficiencies.
This dataset avoids that mistake.

3. Column-by-Column Explanation & Business Meaning

1. Date

Represents the actual transaction date.
Used for:

  • Time intelligence (MTD, QTD, YTD)
  • Cash flow timing
  • Trend and seasonality analysis

In Power BI, this column enables:

  • Rolling 12-month views
  • YoY comparisons
  • Forecast modeling

2. Month

A derived field to simplify:

  • Monthly grouping
  • Executive charts
  • Non-technical stakeholder reporting

While Power BI can derive month names, having it prefilled mirrors real ERP exports.

3. Year

Used for:

  • Annual comparisons
  • Financial year reporting
  • Multi-year growth analysis

Essential for CFO dashboards that compare current vs previous financial year.

4. Department

Identifies the functional owner of the transaction:

  • Sales
  • Marketing
  • Finance
  • Operations
  • HR
  • IT

Utility:

  • Department-wise profitability
  • Cost accountability
  • Budget ownership tracking

CFOs rely heavily on this to identify cost-heavy departments and optimize spend.

5. Cost_Center

Represents structured accounting cost centers (e.g., CC-101, CC-201).

Utility:

  • Budget vs Actual analysis
  • Internal chargeback models
  • Audit and compliance mapping

Cost centers are mandatory in large organizations and are a key CFO control mechanism.

6. Revenue_Stream

Populated only for revenue transactions:

  • Product Sales
  • Subscription
  • Consulting

Utility:

  • Revenue mix analysis
  • Dependency on recurring vs one-time income
  • Strategic planning

Example insight:

“Subscriptions contribute 42% of revenue but only 18% of operational cost.”

7. Transaction_Type

Clearly separates:

  • Revenue
  • Expense

This design choice simplifies:

  • Net profit calculations
  • Waterfall charts
  • Cash flow visuals

CFO dashboards always require a clean revenue–expense split for trust and clarity.

8. Description

Human-readable explanation of the transaction.

Utility:

  • Audit trail
  • Management review
  • Drill-through analysis

This column increases dataset credibility, making it suitable for:

  • Investor decks
  • Board-level demos
  • Training use cases

9. Amount

The core financial value:

  • Positive = Cash In / Revenue
  • Negative = Cash Out / Expense

Utility:

  • Profit calculations
  • Cash flow analysis
  • EBITDA modeling
  • Burn rate analysis

This sign-based approach is common in real finance systems and simplifies DAX.

10. Payment_Mode

Shows how money moved:

  • Bank Transfer
  • Online

Utility:

  • Cash vs digital payment analysis
  • Treasury planning
  • Liquidity forecasting

CFOs use this to:

  • Track reliance on banking channels
  • Optimize payment cycles

11. Project

Links transactions to strategic initiatives such as:

  • CFO Dashboard
  • ERP Upgrade
  • Cloud Migration
  • CRM Rollout

Utility:

  • ROI analysis
  • Project profitability
  • Capital allocation decisions

This column is extremely powerful:

It allows CFOs to answer:
“Which projects actually made us money?”

12. Region

Geographical dimension:

  • North America
  • Europe
  • India
  • Asia Pacific
  • Middle East

Utility:

  • Regional profitability
  • Market expansion decisions
  • Currency risk analysis (if extended)

CFOs use this to decide:

  • Where to invest more
  • Which regions are cost-heavy but underperforming

4. What Makes This Dataset “CFO-Grade”

This dataset is not academic or synthetic-looking. It reflects:

  • Real accounting logic
  • Real cost structures
  • Real revenue behavior

Key strengths:

  • Multi-dimensional (Time, Dept, Project, Region)
  • Clean sign logic for finance modeling
  • Ready for DAX without heavy preprocessing
  • Scalable for forecasts and budgets

It mimics what CFOs expect from monthly MIS or finance warehouse tables.

5. Key Power BI Use Cases Enabled

1. Profit & Loss Dashboard

  • Total Revenue
  • Total Expenses
  • Net Profit
  • Profit Margin %

With drill-down to:

  • Department
  • Project
  • Region

2. Cash Flow Analysis

Using Amount + Date:

  • Cash In vs Cash Out
  • Monthly net cash position
  • Burn rate tracking

This is critical for:

  • Startups
  • CFOs managing working capital
  • Board reporting

3. ROI Analysis

By aggregating:

  • Revenue linked to Project
  • Expenses linked to Project

You can calculate:

  • ROI %
  • Payback period
  • High-performing initiatives

This enables data-driven capital allocation.

4. Department Cost Optimization

Analyze:

  • Expense by Department
  • Expense trend over time
  • Cost vs revenue contribution

CFO insight example:

“Marketing costs rose 22% but revenue impact was only 6%.”

5. Executive KPI Scorecard

Single-page CFO view:

  • Revenue Growth
  • Operating Margin
  • Cash Balance Trend
  • Top 5 Profitable Projects
  • Top 5 Cost Drivers

This dataset supports all of them cleanly.

6. Why This Dataset Is Ideal for Training & Demos

For:

  • Power BI YouTube tutorials
  • Corporate finance training
  • CFO dashboard portfolios
  • Interview case studies

Because:

  • It looks real
  • It behaves like real ERP data
  • It produces believable insights

Hiring managers and clients immediately recognize it as industry-relevant.

7. Scalability & Extensions

This dataset can easily be extended with:

  • Budget table
  • Forecast table
  • Currency column
  • Vendor table
  • Customer table

Making it suitable for:

  • Advanced FP&A models
  • Scenario planning
  • What-if analysis

8. Final Summary

This 300-row financial dataset is a professional, production-style finance table designed to support CFO-level decision-making in Power BI.

It enables:

  • Strategic insight
  • Financial control
  • Executive storytelling
  • Real-world BI modeling

If someone can build a strong dashboard on this dataset, they can confidently handle real corporate finance data.