Project Scope: Transforming a fragmented $13.44M dataset into an Executive-Grade BI Pipeline.
I couldn't just build charts on top of that—the numbers would have been wrong.
Before any visualization could happen, I engineered a robust ETL (Extract, Transform, Load) pipeline using Power Query to sanitize a fragmented dataset of 1,184+ records.
To ensure the $13.44M revenue figure was bulletproof, I executed the following transformations:
- Attribute Standardization: Used
Text.ProperandConditional Columnsto resolve naming conflicts (e.g., merging "TX", "Tex", and "Texas" into a single "Texas" attribute) for accurate regional grouping. - Data Type Enforcement: Audited and corrected mixed-type errors in the "Revenue" and "Date" columns, preventing calculation breaks in the backend Pivot models.
- Deduplication & Null Handling: Identified and removed 12+ "ghost" records and handled null values in the Lead Source column to prevent skewed ROI metrics.
- Schema Optimization: Transformed a wide, flat table into a clean, analysis-ready schema by removing redundant metadata and enforcing strict column headers.
Before & After: Data Transformation
| Raw Unstructured Input | Cleaned & Standardized Output |
|---|---|
 |
 |
With a clean dataset, I built a relational backend using multiple Pivot Table Models. The goal wasn't just a static report, but a Dynamic Decision Tool that allows leadership to stress-test the $13.44M pipeline from three critical angles.
The Analysis: A granular audit of individual performance across the sales force to identify high-performers vs. coaching opportunities.
- The Solution: This pivot tracks the "Middle of the Funnel." It identifies which reps are successfully converting high-value deals versus those stalled in the "Discovery" phase. This allows management to move away from generic meetings and toward targeted data decisions.
The Analysis: An audit of Lead Quality to ensure every dollar of the $13.44M pipeline is being spent on the right channels.
- The Solution: By calculating the conversion rate per vendor, I identified that while VoltEdge provided the highest volume (43%), SunLead Pro delivered an 18% higher ROI per lead. This insight provides the evidence needed for strategic budget reallocation.
The Analysis: A high-level view of Market Penetration across the US to find untapped growth.
- The Solution: This view isolates revenue by State and Region. It revealed that the Midwest was hitting a 52% conversion rate—significantly outperforming the national average—signaling a prime geographical area for team expansion and increased marketing spend.
The Connector: All three engines are tied to a Global Slicer Panel. A single click on a "Region" or "Manager" slicer updates all three views simultaneously, providing an instant, 360-degree audit of any business segment.
The final layer of the project is a high-fidelity Executive Dashboard designed for C-Suite decision-making. By applying a "No-Grid" UI/UX approach, I transformed a standard spreadsheet into a functional business application that provides a $13.44M bird’s-eye view.
I synthesized the entire $13.44M pipeline into a final audit of Conversion Strategy and Growth Benchmarks.
- The High-Level Audit: Confirmed a total revenue of $13.44M with a healthy 48% conversion rate across all channels.
- Lead Quality Variance: Discovered that despite VoltEdge contributing 43.1% of lead volume, they lagged behind SunLead Pro in ROI per lead—proving that volume doesn't always equal value.
- Geographical Dominance: Identified the Midwest as the top-performing region, consistently hitting a 52% conversion rate, making it the primary target for further marketing spend.
The Technical Polish: I implemented custom number formatting (
$#,,.00"M") for clarity, zero-border charting for a modern UI, and dynamic KPI cards that update instantly when sliced by Representative or Region.
The Big Number: A crystal clear $13.44M total revenue KPI.
Conversion Truths: Discovered we have a rock-solid 48% conversion rate, but some "high volume" vendors were actually underperforming on quality.
Custom UI: Used custom formatting ($0.00"M") so the C-suite doesn't have to squint at long strings of zeros.
- Download the Master Analysis File (.xlsx)
- Open the file and navigate to the Executive Dashboard tab.
- Use the integrated Slicers to filter by Region, Lead Vendor, or Sales Representative.
- Data Visualization: KPI Card Design, Dynamic Slicers, Custom Number Formatting, UI/UX for Executive Reporting.
- ETL & Data Cleaning: Power Query, Data Validation, Error Identification, Standardizing Categorical Data.
- Business Intelligence: Pivot Table Logic, Multi-Dimensional Filtering, ROI Analysis, Lead Conversion Tracking.
- Domain Knowledge: Sales Operations, Revenue Intelligence, CRM Data Audit.
If you have questions about the logic behind this $13.44M audit or want to discuss Data Analyst opportunities, feel free to reach out!
- LinkedIn: Nakul Sachdeva
- Portfolio: Check out my other projects
- Email: [nakulsachdeva.careers@gmail.com]