This dataset contains a list of sales and movement data by item and department appended monthly. Update Frequency : Monthly

This dataset offers a valuable resource for businesses operating in the retail furniture sector. By analyzing historical sales data from the superstore dataset, users can gain insights into future sales patterns and trends. This information can be utilized to optimize inventory management strategies, anticipate customer demand, and enhance overall operational efficiency. Whether for retail managers, analysts, or data scientists, this dataset provides a foundation for informed decision-making, helping businesses maintain stability and drive sustained growth in the dynamic retail environment.

This fictional sales dataset was created using a R code for the purpose of visualizing trends in customer demographics, product performance, and sales over time. A link to my Github repository containing all the codes used in generating the data frame and all the preceding processes can be found here

Context

This synthetic sales dataset was created to simulate real-world business transactions and provide a practical dataset for learning and building data analytics projects.

It contains transaction-level sales data across multiple years, covering areas such as customers, products, locations, sales channels, pricing, discounts, payments, revenue, and profit.

The dataset is suitable for Excel, SQL, Python/Pandas, Power BI, Tableau, and R/RStudio.

Inspiration

Real business sales data can be difficult to access because of privacy and confidentiality. This dataset was created as a safe alternative for students, analysts, and aspiring data professionals to practice working with realistic business data.

It also includes some missing, inconsistent, or unusual values so users can practice real-world data cleaning and validation.

What You Can Analyze

The dataset can be used to explore questions such as:

• How do sales change over time?
• Which products and categories perform best?
• Which regions generate the most revenue?
• How do discounts affect profit?
• Which sales channels perform best?
• What are the most profitable products?
• Are there seasonal sales patterns?
• Which areas or products are underperforming?

Common KPIs include Revenue, Profit, Profit Margin, Quantity Sold, Transactions, and Average Order Value.

Usage

This dataset is suitable for:

• Data cleaning and preparation
• Exploratory Data Analysis (EDA)
• SQL analysis
• Sales and customer analysis
• Business intelligence dashboards
• Statistical analysis
• Portfolio projects

* Machine learning experiments

Data Quality

The dataset intentionally contains some realistic data-quality issues, such as missing values, inconsistent entries, and unusual records, making it useful for demonstrating the complete analytics process:

Raw Data → Cleaning → Analysis → Visualization → Insights → Recommendations

Important Note

This is a fully synthetic dataset created for educational and portfolio purposes. It does not contain real customer, company, or financial information.

This dataset contains data on all Real Property parcels that have sold since 2013 in Allegheny County, PA.

Before doing any market analysis on property sales, check the sales validation codes. Many property "sales" are not considered a valid representation of the true market value of the property. For example, when multiple lots are together on one deed with one price they are generally coded as invalid ("H") because the sale price for each parcel ID number indicates the total price paid for a group of parcels, not just for one parcel. See the Sales Validation Codes Dictionary for a complete explanation of valid and invalid sale codes.

Sales Transactions Disclaimer: Sales information is provided from the Allegheny County Department of Administrative Services, Real Estate Division. Content and validation codes are subject to change. Please review the Data Dictionary for details on included fields before each use. Property owners are not required by law to record a deed at the time of sale. Consequently the assessment system may not contain a complete sales history for every property and every sale. You may do a deed search at http://www.alleghenycounty.us/re/index.aspx directly for the most updated information. Note: Ordinance 3478-07 prohibits public access to search assessment records by owner name. It was signed by the Chief Executive in 2007.

Retail Sales in Romania increased 0.80 percent in July of 2026 over the previous month. This dataset provides - Romania Retail Sales MoM - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Existing Home Sales in Ireland increased to 3418 Units in July from 2973 Units in June of 2026. This dataset provides - Ireland Existing Home Sales- actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset contains sample e-commerce sales records for practicing data analysis, business intelligence, and data visualization. It is suitable for Power BI dashboards, SQL queries, Excel analysis, Python projects, and machine learning preprocessing exercises.

Retail Sales Food and Beverage Stores MoM in the United States increased to 0.40 percent in August from -0.20 percent in July of 2026. This dataset includes a chart with historical data for the United States Retail Sales Food And Beverage Stores MoM.

This dataset offers a comprehensive view of a retail distribution network in Bangladesh, encompassing three interconnected aspects: product sales targets, product information, and shop demographics. The data is spread across three CSV files, each serving a distinct purpose: 1. product target for shop.csv contains sales targets for 18 different products across 613,656 unique shops, identified by a unique shop code. This file allows for analysis of product-specific sales goals at the individual shop level. 2. product info.csv provides detailed information about the products, including their SKU IDs, names, brands, types, pricing structures, and physical characteristics. This file offers insights into the product portfolio, including 5 brands, 9 product types, and various packaging options. 3. shop info.csv presents demographic and geographic information about each shop in the network. It includes data on shop location (down to latitude and longitude), administrative divisions (division, zila, upazila), shop categorization (type, style, importance), and operational details (visit frequency, organizer). Together, these files create a multi-dimensional picture of the retail landscape, enabling researchers to explore relationships between product characteristics, shop attributes, geographic location, and sales targets. This rich dataset provides a foundation for analyses ranging from market segmentation and product placement strategies to geospatial distribution patterns and supply chain optimization.

Graph and download economic data for Monthly State Retail Sales: Furniture and Home Furnishings Stores in Arizona (MSRSAZ442) from Jan 2019 to May 2026 about furniture, AZ, retail trade, sales, retail, housing, and USA.

From 2019 to 2023, the total retail sales value of the health supplements market in Hong Kong increased by *** percent to ** billion Hong Kong dollars. Online retail channels, though accounted for a fraction, showed a faster growth. Retail sales value of offline health supplements was expected to reach **** billion Hong Kong dollars by 2028.

Retail sales index in Romania, August, 2026 The most recent value is 113.7 index points as of August 2026, an increase compared to the previous value of 111.1 index points. Historically, the average for Romania from January 2000 to August 2026 is 65.59 index points. The minimum of 23.6 index points was recorded in April 2001, while the maximum of 119.1 index points was reached in June 2025. | TheGlobalEconomy.com

Historical e-Commerce comparable sales data for Costco Wholesale Corporation, covering Comparable Sales and Comparable Sales excluding Impact of FX & Gas, covering fiscal year 2020 through 2025 for Comparable Sales, and fiscal years 2021 through 2025 for Comparable Sales excluding Impact of FX & Gas, expressed as a percentage.

Retail Sales: Other Services data was reported at 75,907.668 VND bn in Sep 2026. This records an increase from the previous number of 73,395.312 VND bn for Aug 2026. Retail Sales: Other Services data is updated monthly, averaging 44,568.549 VND bn from Jan 2010 (Median) to Sep 2026, with 199 observations. The data reached an all-time high of 75,907.668 VND bn in Sep 2026 and a record low of 11,273.432 VND bn in Jul 2010. Retail Sales: Other Services data remains active status in CEIC and is reported by National Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.H: Retail Sales.

Retail Sales in Slovakia increased 1.60 percent in August of 2026 over the same month in the previous year. This dataset provides - Slovakia Retail Sales YoY - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Retail Sales of Consumer Goods: Heilongjiang: Daqing data was reported at 64.020 RMB bn in 2025. This records an increase from the previous number of 61.470 RMB bn for 2024. Retail Sales of Consumer Goods: Heilongjiang: Daqing data is updated yearly, averaging 58.949 RMB bn from Dec 1996 (Median) to 2025, with 29 observations. The data reached an all-time high of 124.779 RMB bn in 2018 and a record low of 6.413 RMB bn in 1997. Retail Sales of Consumer Goods: Heilongjiang: Daqing data remains active status in CEIC and is reported by Daqing Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HE: Retail Sales of Consumer Goods: Prefecture Level City.

As of fisrt half of 2025, around ******* units of vehicles including passenger cars and commercial vehicles were sold in South Korea. Domestic car sales were on a slight decrease after the COVID-19 pandemic.

Retail Sales - Table 620-67001 : Total retail sales

Key information about Bosnia and Herzegovina Retail Sales Growth

• Bosnia and Herzegovina Retail Sales grew 9.0 % YoY in Oct 2025, compared with a 3.7 % increase in the previous month.
• Bosnia and Herzegovina Retail Sales Growth YoY data is updated monthly, available from Jan 2013 to Oct 2025, with an average growth rate of -0.7 %.
• The data reached an all-time high of 46.6 % in Apr 2021 and a record low of -34.6 % in Apr 2020.
• In the latest reports, Car Sales of Bosnia and Herzegovina recorded 11,358.0 units in Dec 2019, representing a drop of 52.5 %.