An Excel-to-Power BI sales analytics project for reviewing order data, preparing a reliable model and presenting business-focused insights.

Overview • Preview • Highlights • Files • Uses • Workflow • Start • Guide • Security • Author

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🎯 Project Overview

Sales Data Analysis — Assessment 11 is a compact portfolio and assessment project that connects an order-level dataset in Microsoft Excel with an analytical report in Microsoft Power BI.

The repository demonstrates a practical end-to-end workflow:

• reviewing and organising source data;
• identifying blanks, duplicates, invalid values and inconsistent formats;
• preparing repeatable transformations through Power Query;
• reviewing the Power BI data model, relationships and filter behaviour;
• validating report totals against the Excel source;
• presenting sales information through structured visuals; and
• documenting the project for learning, assessment and portfolio use.

Project category: Data analytics assessment and portfolio demonstration.

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🖥️ Project Preview

The visual above is a designed project overview, not an exported screenshot from the PBIX file. Download and open eOrderid_powerbi.pbix in Microsoft Power BI Desktop to view the actual interactive report.

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✨ Project Highlights

Capability	What this project demonstrates
📗 Excel source management	Reviewing the structure, data types, records, formulas, links and source quality of Orders.xlsx.
🧹 Data preparation	Cleaning and standardising the source before it is used for reporting.
🔄 Power Query	Building or reviewing repeatable transformation steps and repairing the local source path when required.
🧩 Data modelling	Checking relationships, aggregation logic, measures, filters and model behaviour.
📊 Dashboard validation	Comparing KPIs and chart totals with the validated Excel source.
🧠 Business interpretation	Turning available sales and order information into clear, supportable observations.
📁 Portfolio documentation	Presenting files, usage instructions, security guidance and project scope professionally on GitHub.

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📁 Repository Contents

File	Type	Purpose
Orders.xlsx	Excel workbook	Source sales and order dataset used by the project.
eOrderid_powerbi.pbix	Power BI report	Interactive report and analytics model built from the Excel source.
HOW_TO_USE.md	Detailed guide	Setup, cleaning, refresh, validation, analysis, reuse and troubleshooting instructions.
assets/cover/sales-data-cover.svg	Cover visual	Repository-native fallback cover retained with the project assets.
assets/preview/project-preview.svg	Preview visual	Designed overview of the intended analytics experience.
SECURITY.md	Security policy	Responsible disclosure, privacy and safe binary-file usage guidance.
LICENSE	MPL 2.0	Terms governing use and distribution of the repository content.

Clean folder structure

sales-data-a11/
├── data/
│   └── raw/
│       └── Orders.xlsx
├── reports/
│   └── power-bi/
│       └── eOrderid_powerbi.pbix
├── docs/
│   └── HOW_TO_USE.md
├── assets/
│   ├── cover/
│   │   └── sales-data-cover.svg
│   └── preview/
│       └── project-preview.svg
├── README.md
├── SECURITY.md
└── LICENSE

The root directory is intentionally limited to GitHub-standard project files. Dataset, report, documentation and visual assets are separated by purpose for faster navigation and cleaner downloads.

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💡 Best Ways to Use This Project

Goal	Recommended use
Learn Excel data preparation	Review headers, dates, numeric fields, categories, blanks, duplicates and unusual values.
Practise Power Query	Inspect, rename and improve repeatable transformation steps.
Develop Power BI skills	Review sources, relationships, measures, filters, visuals and report navigation.
Perform sales analysis	Explore trends, order behaviour and any product, customer, channel or geographic fields available in the source.
Build a portfolio case study	Present a complete Excel-to-Power BI workflow with documentation and validation controls.
Complete an assessment	Rebuild, explain, validate or extend the report as a structured analytics exercise.
Test a compatible dataset	Replace sample rows while preserving the expected schema and then validate the refreshed model.
Improve data governance	Document KPI definitions, assumptions, data-quality decisions, limitations and privacy controls.

The exact analysis depends on the fields contained in Orders.xlsx. Findings should not exceed what the validated data can support.

📘 Read the full HOW_TO_USE.md guide for detailed procedures and troubleshooting.

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🔄 Analytics Workflow

flowchart LR
    A[Orders.xlsx<br/>Source Data] --> B[Review &<br/>Clean]
    B --> C[Power Query<br/>Transform]
    C --> D[Power BI<br/>Model]
    D --> E[Interactive<br/>Report]
    E --> F[Validate &<br/>Interpret]

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Recommended sequence

1. Download the official project files.
2. Create a backup working copy.
3. Review and clean Orders.xlsx.
4. Open eOrderid_powerbi.pbix in Power BI Desktop.
5. Repair the Excel source path when necessary.
6. Refresh Power Query and the data model.
7. Validate every KPI, filter and visual.
8. Document insights, assumptions and limitations.

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🧰 Tools and Capabilities

Area	Technology / Capability
Data source	Microsoft Excel (.xlsx)
Reporting	Microsoft Power BI Desktop (.pbix)
Data preparation	Data review, cleaning, transformation and validation
Modelling	Relationships, measures, calculated logic and filter context
Analysis	Sales and order-level exploratory analysis
Visualisation	KPI cards, charts, filters, interactions and report pages
Documentation	Markdown-based project, usage and security guidance

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🚀 Quick Start

Option 1 — Clone the repository

git clone https://github.com/samusa099/sales-data-a11.git
cd sales-data-a11

Option 2 — Download the main files

• ⬇️ Download Orders.xlsx
• ⬇️ Download eOrderid_powerbi.pbix
• 📘 Open HOW_TO_USE.md

Open and review

1. Download the two main project files from their structured folders.
2. Keep Orders.xlsx and eOrderid_powerbi.pbix together in a private local working folder.
3. Inspect the Excel workbook before refreshing the report.
4. Open the PBIX file in Microsoft Power BI Desktop.
5. Go to File → Options and settings → Data source settings if the workbook path is broken.
6. Point the report to the local working copy of Orders.xlsx.
7. Refresh the queries and data model.
8. Compare critical report totals with validated Excel calculations.

GitHub cannot preview a .pbix file directly. It must be downloaded and opened with Power BI Desktop.

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✅ Review Checklist

• The source workbook has been backed up.
• Column names and data types are consistent.
• Blank, duplicate and invalid records have been reviewed.
• Excel formulas, named ranges, links and connections are understood.
• Power BI points to the intended workbook.
• Power Query refreshes without errors.
• Model relationships and aggregation methods are appropriate.
• KPI cards and charts match validated source calculations.
• Slicers, filters and interactions work as expected.
• No credentials, personal records or confidential business data are included.

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🔐 Security & File Safety

This repository distributes binary Microsoft Excel and Power BI files. Download them only from the official repository and inspect their connections and embedded content before using confidential or production data.

Area	Recommended action
Download source	Use only the official samusa099/sales-data-a11 repository.
Excel workbook	Review formulas, named ranges, external links and data connections before enabling refresh.
Power BI report	Review Power Query sources, data-source settings, refresh credentials and custom visuals.
Credentials	Never commit passwords, access tokens, gateway credentials or connection strings.
Data privacy	Use synthetic, anonymised or properly authorised data only.
Reporting	Do not publish sensitive vulnerability details in a public issue.

Read the complete SECURITY.md policy for supported repository versions, responsible reporting, severity classification and remediation guidance.

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📄 License

This project is distributed under the Mozilla Public License 2.0. See LICENSE for the complete terms.

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👤 Author

MUSA
HR Professional • Data Analytics Practitioner
Building practical, business-focused insights with Excel and Power BI.

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🌟 Practical analytics. Clear documentation. Business-focused learning.

⭐ Star the repository if this project is useful to you.