---
title: "Discussion on \"Enhanced Sales Insights with a Dashboard Built on Power Pivot and DAX\" | Hashnode"
description: "Discussion on \"Enhanced Sales Insights with a Dashboard Built on Power Pivot and DAX\". Discover how to enhance sales insights using Power Pivot and DAX for effective data modeling, dashboard creation, and KPI analysis"
url: "https://hashnode.com/posts/enhanced-sales-insights-with-a-dashboard-built-on-power-pivot-and-dax/681b0f620871568a9f76c64d"
---

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# [Enhanced Sales Insights with a Dashboard Built on Power Pivot and DAX](https://excel-analysis.hashnode.dev/enhanced-sales-insights-with-a-dashboard-built-on-power-pivot-and-dax?utm_source=hashnode&utm_medium=feed)

Discover how to enhance sales insights using Power Pivot and DAX for effective data modeling, dashboard creation, and KPI analysis

May 7, 2025 · 7 min read · excel-analysis.hashnode.dev  
Updated Aug 27, 2025  
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-   [#excelanalysis](https://hashnode.com/tag/excelanalysis)
-   [#finance](https://hashnode.com/tag/finance)
-   [#powerquery](https://hashnode.com/tag/powerquery)
-   [#powerpivot](https://hashnode.com/tag/powerpivot)

## Written by

[Jogleen Calipon](https://hashnode.com/@Jworkz)

@Jworkz · Calabarzon, Philippines

  
[View profile](https://hashnode.com/@Jworkz)

Power Query and Power Pivot Specialist

📊 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 | 𝗣𝗼𝘄𝗲𝗿 𝗦𝘂𝗶𝘁𝗲 𝗦𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘀𝘁 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗿𝗮𝘄 𝗱𝗮𝘁𝗮 𝗶𝗻𝘁𝗼 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲. I am a Data Analyst with 4+ years of experience specializing in the Microsoft ecosystem. I bridge the gap between messy data and executive decisions. ────────────── 💎 𝗖𝗼𝗿𝗲 𝗦𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 ➤ 1. Advanced Power Query (ETL) Expert at cleaning &amp; enriching datasets in Excel &amp; Power BI. Building "one-click" refresh workflows. ➤ 2. Modeling &amp; DAX (Power Pivot) Designing robust data models and applying DAX for KPIs &amp; Time-Intelligence. ➤ 3. Strategic Visualization Developing interactive Power BI dashboards with actionable storytelling for decision-makers. ────────────── 🛠️ 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗧𝗼𝗼𝗹𝗸𝗶𝘁 (Foundational) • Databases: SQL Server (SSMS), MySQL, BigQuery, MS Access. • Coding: Python (Pandas/NumPy), R (ggplot2).

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