This data set is perfect for practicing your analytical skills for Power BI, Tableau, Excel, or transform it into a CSV to practice SQL.

This use case mimics transactions for a fictional eCommerce website named EverMart Online. The 3 tables in this data set are all logically connected together with IDs.

My Power BI Use Case Explanation - Using Microsoft Power BI, I made dynamic data visualizations for revenue reporting and customer behavior reporting.

Revenue Reporting Visuals - Data Card Visual that dynamically shows Total Products Listed, Total Unique Customers, Total Transactions, and Total Revenue by Total Sales, Product Sales, or Categorical Sales. - Line Graph Visual that shows Total Revenue by Month of the entire year. This graph also changes to calculate Total Revenue by Month for the Total Sales by Product and Total Sales by Category if selected. - Bar Graph Visual showcasing Total Sales by Product. - Donut Chart Visual showcasing Total Sales by Category of Product.

Customer Behavior Reporting Visuals - Data Card Visual that dynamically shows Total Products Listed, Total Unique Customers, Total Transactions, and Total Revenue by Total or by continent selected on the map. - Interactive Map Visual showing key statistics for the continent selected. - The key statistics are presented on the tool tip when you select a continent, and the following statistics show for that continent: - Continent Name - Customer Total - Percentage of Products Sold - Percentage of Total Customers - Percentage of Total Transactions - Percentage of Total Revenue

Hello Everyone, I made this Finance Dashboard in Power BI with the Finance Excel Workbook provided by Microsoft on their Website. Problem Statement The goal of this Power BI Dashboard is to analyze the financial performance of a company using the provided Microsoft Sample Data. To create a visually appealing dashboard that provides an overview of the company's financial metrics enabling stakeholders to make informed business decisions. Sections in the Report Report has multiple section's from where you can manage the data, like : • Report data can be sliced by Segments, Country and Year to show particular data. - Report Contain Two Navigation Page one is overview and other is sales dashboard page for better visualisation of data. - Report Contain all the important data. - Report Contain different chart and bar garph for different section .

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The previously published Management Information released October 2023 was replaced in December 2023 and the 'National Statistics' and ‘Official Statistics’ designation reinstated. The December release also includes publication commentary, data quality tables and a PowerBI interactive tool. Data remains the same except for the addition of Data Tables T4, 12, 16, 24, 32, 36 and 51. This publication contains data taken from the Adult Social Care Finance Return (ASC-FR) and Short and Long Term (SALT) collection to provide information regarding adult social care activity and finance on Councils with Adult Social Services Responsibilities (CASSRs) in England for 2022-23. CASSRs will be referred to as local authorities throughout this report. Aggregate data is mandated to be collected from 152 local authorities in England, to provide insight into adult social care activity and expenditure for the period 1 April 2022 to 31 March 2023.

The October release includes publication commentary, zipped comma-separated values (CSV) data pack, data quality tables and a Power BI interactive tool. This publication contains data taken from the Adult Social Care Finance Return (ASC-FR) and Short and Long Term (SALT) collection to provide information regarding adult social care activity and finance on Councils with Adult Social Services Responsibilities (CASSRs) in England for 2023-24. CASSRs will be referred to as local authorities throughout this report. Aggregate data is mandated to be collected from 153 local authorities in England, to provide insight into adult social care activity and expenditure for the period 1 April 2023 to 31 March 2024.

Context

I made a couple or reports using Power BI and the open data site of Iowa State.

Content

Youw ill have to download the data set from the Iowa's web site. The model have a simple charts and table to visualize the sales of Liquor.

https://data.iowa.gov/Sales-Distribution/Iowa-Liquor-Sales/m3tr-qhgy.

Acknowledgements

Inspiration

This dataset contains sales transaction records used to create an interactive Excel Sales Performance Dashboard for business analytics practice.

It includes six columns capturing essential sales metrics such as date, region, product, quantity, sales revenue, and profit. The data is structured to help analysts and learners explore data visualization, PivotTable summarization, and dashboard design concepts in Excel.

The dataset was created for educational and demonstration purposes to help users:

1. Build dashboards that visualize total sales and profit trends
2. Identify top-performing products and high-profit regions
3. Practice Excel-based business analytics workflows

Columns: Date – Transaction date (daily sales record) Region – Geographic area of the sale (East, West, North, South) Product – Product category or item sold Sales – Total revenue generated from the sale (USD) Profit – Net profit made per transaction Quantity – Number of units sold

Typical uses include: Excel or Power BI dashboard projects PivotTable practice for business reporting Data cleaning and chart-building exercises Portfolio development for business analytics students Built and tested in Microsoft Excel using PivotTables, Charts, and Conditional Formatting.

This dataset is prepared using random number generator function in excel. The data include sample bank branch key business parameters.

3 dim tables include key business parameters, dates and branch names. 3 fact tables include parameter values of branches as on 3 different dates (last FY end,last Qtr end, last day).

The dataset can be loaded into Power BI for analysis and visualizations. 3 fact tables can be appended to one table. 3 types of reports can be generated : Branch-wise Business , Trend analysis , Parameter-wise analysis

Image Credits: (Image by pch.vector on Freepik)

🧥 Snitch Fashion Sales (Uncleaned) Dataset 📌 Context This is a synthetic dataset representing sales transactions from Snitch, a fictional Indian clothing brand. The dataset simulates real-world retail sales data with uncleaned records, designed for learners and professionals to practice data cleaning, exploratory data analysis (EDA), and dashboard building using tools like Python, Power BI, or Excel.

📊 What You’ll Find The dataset includes over 2,500 records of fashion product sales across various Indian cities. It contains common data issues such as:

Missing values

Incorrect date formats

Duplicates

Typos in categories and city names

Unrealistic discounts and profit values

🧾 Columns Explained Column --Description Order_ID ------Unique ID for each sale (some duplicates) Customer_Name ------Name of the customer (inconsistent formatting) Product_Category ---Clothing category (e.g., T-Shirts, Jeans — includes typos) Product_Name -----Specific product sold Units_Sold --Quantity sold (some negative or null) Unit_Price --Price per unit (some missing or zero) Discount_% ----Discount applied (some >100% or missing) Sales_Amount ------Total revenue after discount (some miscalculations) Order_Date ---------Order date (multiple formats or missing) City -------Indian city (includes typos like "Hyd", "bengaluru") Segment----- Market segment (B2C, B2B, or missing) Profit ---------Profit made on the sale (some unrealistic/negative)

💡 How to Use This Dataset Clean and standardize messy data

Convert dates and correct formats

Perform EDA to find:

Top-selling categories

Impact of discounts on sales and profits

Monthly/quarterly trends

Segment-based performance

Create dashboards in Power BI or Excel Pivot Table

Document findings in a PDF/Markdown report

🎯 Ideal For Aspiring data analysts and data scientists

Excel / Power BI dashboard learners

Portfolio project creators

Kaggle competitions or practice

📌 License This is a synthetic dataset created for educational use only. No real customer or business data is included.