Dark Mode
Business Operations Analytics Dataset
Data Science and Analytics
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset provides a detailed overview of business operations, offering valuable information and insights for analysis. It is designed to facilitate visualisation and understanding of various business metrics. The data is typically generated from diverse business sources such as financial statements, sales reports, market research studies, and online analytics tools. It is collected and analysed by businesses to inform decision-making, optimise operations, and enhance overall performance.
Columns
- Ship: Describes the shipping class. Most common classes include 'Standard' (60%) and 'Second' (19%).
- Class: General classification information. Common entries include 'Class' (95%) and 'Day' (5%).
- Segment: Indicates the customer type or segment. Most common segments are 'Consumer' (52%) and 'Corporate' (30%).
- Country: The name of the country. Common entries include 'United' (82%) and 'Office' (18%).
- City: The name of the city. Common entries include 'States' (82%) and 'United' (18%).
- State: The name of the state. Common entries include 'States' (18%) and 'New' (8%).
- Postal: Geographic postal identifier. Most common entries include 'York' (8%) and 'Texas' (7%).
- Code: Alphanumeric code, potentially a part of an address or identification. Most common entries include 'California' (14%) and 'City' (8%).
- Region: Geographic region. Most common regions are 'Central' (16%) and 'East' (12%).
- Category: Product category. Most common categories are 'Office' (29%) and 'West' (17%).
- Sub-Category: More specific product sub-category. Most common sub-categories are 'Supplies' (29%) and 'Office' (21%).
- Sales: Sales figures. Common entries mentioned in the data include 'Supplies' (22%) and 'East' (8%).
- Quantity: Product quantities. Common entries mentioned include 'Binders' (5%) and 'Paper' (5%).
- Discount: Discount applied to sales. Common values are '2' (11%) and '3' (11%).
- Profit: Profit generated from sales. Common values are '0.2' (19%) and '0' (18%). The profit data has a mean of 52.2, a standard deviation of 227, and ranges from -103 to 3.92k.
Distribution
The dataset is provided in a CSV file format, specifically 'SampleSuperstore.csv', with a size of 1.05 MB. It comprises 16 distinct columns. The data contains 9994 valid records for most columns, with no mismatched or missing values in the majority of fields. For the 'Profit' analysis, 629 (6%) valid records are present, with 9365 (94%) missing values within that specific statistical view.
Usage
This dataset is ideal for:
- Creating visualisations to gain insights into business performance.
- Supporting informed decision-making processes within organisations.
- Optimising business operations.
- Improving overall business performance through data-driven strategies.
- Market research and sales analysis.
Coverage
The geographic scope includes information on Country (e.g., United), City (e.g., States), State (e.g., States, New), and Region (e.g., Central, East), suggesting a focus primarily on the United States, with regional breakdowns. The demographic scope is covered by the 'Segment' column, which differentiates between 'Consumer' and 'Corporate' types. A time range is not explicitly specified within the provided source materials. Most columns have 9994 valid data entries, indicating a consistent level of data availability across many fields.
License
CC0: Public Domain
Who Can Use It
- Businesses: To make data-driven decisions, streamline operations, and enhance their market position.
- Data Analysts: For exploring trends, creating reports, and developing predictive models.
- Researchers: To study market dynamics, consumer behaviour, and operational efficiencies.
- Students: As a practical resource for learning data analysis and business intelligence.
Dataset Name Suggestions
- Business Operations Analytics Dataset
- Superstore Performance Data
- Global Retail Insights Data
- Organisational Performance Metrics
Attributes
Original Data Source: Business Operations Analytics Dataset
QUALITY