• Dataset Title: Company Purchasing Dataset
• Rows: 500 | Columns: 9
• Domain: Supply Chain, Procurement, Finance
• Use Case: Spend Analytics, Supplier Performance, Cost Optimization

This synthetic dataset simulates procurement transactions for a mid-sized organization over 2024. It includes purchases across multiple categories (electronics, furniture, stationery, etc.) from various suppliers and buyers. Ideal for practicing descriptive analytics, spend analysis, and supplier performance evaluation.

With 56 Million Businesses in the United States of America, Techsalerator has access to the highest B2B count of Data/ Business Data in the country.

Thanks to our unique tools and large data specialist team, we are able to select the ideal targeted dataset based on the unique elements such as sales volume of a company, the company's location, no. of employees etc...

Whether you are looking for an entire fill install, access to our API's or if you are just looking for a one-time targeted purchase, get in touch with our company and we will fulfill your international data need.

We cover all states and cities in the country : Example covered.

All states :

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Dataset

This dataset was created by Atta Chakki ML

Released under Apache 2.0

Contents

With 1.9 Million Businesses in Hong Kong , Techsalerator has access to the highest B2B count of Data/Business Data in the country. .

Thanks to our unique tools and large data specialist team, we can select the ideal targeted dataset based on the unique elements such as sales volume of a company, the company's location, no. of employees etc...

Whether you are looking for an entire fill install, access to our API's or if you are just looking for a one-time targeted purchase, get in touch with our company and we will fulfill your international data need.

We cover all regions and cities in Hong Kong : ( example) Kowloon Northern Hong Kong Island Tsuen Wan New Town Sha Tin New Town Tuen Mun New Town Tseung Kwan O New Town Aberdeen Tai Po New Town Tin Shui Wai New Town Fanling-Sheung Shui New Town Yuen Long New Town North Lantau New Town

Success.ai’s Company Data Solutions provide businesses with powerful, enterprise-ready B2B company datasets, enabling you to unlock insights on over 28 million verified company profiles. Our solution is ideal for organizations seeking accurate and detailed B2B contact data, whether you’re targeting large enterprises, mid-sized businesses, or small business contact data.

Success.ai offers B2B marketing data across industries and geographies, tailored to fit your specific business needs. With our white-glove service, you’ll receive curated, ready-to-use company datasets without the hassle of managing data platforms yourself. Whether you’re looking for UK B2B data or global datasets, Success.ai ensures a seamless experience with the most accurate and up-to-date information in the market.

Why Choose Success.ai’s Company Data Solution? At Success.ai, we prioritize quality and relevancy. Every company profile is AI-validated for a 99% accuracy rate and manually reviewed to ensure you're accessing actionable and GDPR-compliant data. Our price match guarantee ensures you receive the best deal on the market, while our white-glove service provides personalized assistance in sourcing and delivering the data you need.

Why Choose Success.ai?

• Best Price Guarantee: We offer industry-leading pricing and beat any competitor.
• Global Reach: Access over 28 million verified company profiles across 195 countries.
• Comprehensive Data: Over 15 data points, including company size, industry, funding, and technologies used.
• Accurate & Verified: AI-validated with a 99% accuracy rate, ensuring high-quality data.
• Real-Time Updates: Stay ahead with continuously updated company information.
• Ethically Sourced Data: Our B2B data is compliant with global privacy laws, ensuring responsible use.
• Dedicated Service: Receive personalized, curated data without the hassle of managing platforms.
• Tailored Solutions: Custom datasets are built to fit your unique business needs and industries.

Our database spans 195 countries and covers 28 million public and private company profiles, with detailed insights into each company’s structure, size, funding history, and key technologies. We provide B2B company data for businesses of all sizes, from small business contact data to large corporations, with extensive coverage in regions such as North America, Europe, Asia-Pacific, and Latin America.

Comprehensive Data Points: Success.ai delivers in-depth information on each company, with over 15 data points, including:

Company Name: Get the full legal name of the company. LinkedIn URL: Direct link to the company's LinkedIn profile. Company Domain: Website URL for more detailed research. Company Description: Overview of the company’s services and products. Company Location: Geographic location down to the city, state, and country. Company Industry: The sector or industry the company operates in. Employee Count: Number of employees to help identify company size. Technologies Used: Insights into key technologies employed by the company, valuable for tech-based outreach. Funding Information: Track total funding and the most recent funding dates for investment opportunities. Maximize Your Sales Potential: With Success.ai’s B2B contact data and company datasets, sales teams can build tailored lists of target accounts, identify decision-makers, and access real-time company intelligence. Our curated datasets ensure you’re always focused on high-value leads—those who are most likely to convert into clients. Whether you’re conducting account-based marketing (ABM), expanding your sales pipeline, or looking to improve your lead generation strategies, Success.ai offers the resources you need to scale your business efficiently.

Tailored for Your Industry: Success.ai serves multiple industries, including technology, healthcare, finance, manufacturing, and more. Our B2B marketing data solutions are particularly valuable for businesses looking to reach professionals in key sectors. You’ll also have access to small business contact data, perfect for reaching new markets or uncovering high-growth startups.

From UK B2B data to contacts across Europe and Asia, our datasets provide global coverage to expand your business reach and identify new markets. With continuous data updates, Success.ai ensures you’re always working with the freshest information.

Key Use Cases:

• Targeted Lead Generation: Build accurate lead lists by filtering data by company size, industry, or location. Target decision-makers in key industries to streamline your B2B sales outreach.
• Account-Based Marketing (ABM): Use B2B company data to personalize marketing campaigns, focusing on high-value accounts and improving conversion rates.
• Investment Research: Track company growth, funding rounds, and employee trends to identify investment opportunities or potential M&A targets.
• Market Research: Enrich your market intelligence initiatives by gain...

Overview

This dataset contains a collection of over 2,000 company documents, categorized into four main types: invoices, inventory reports, purchase orders, and shipping orders. Each document is provided in PDF format, accompanied by a CSV file that includes the text extracted from these documents, their respective labels, and the word count of each document. This dataset is ideal for various natural language processing (NLP) tasks, including text classification, information extraction, and document clustering.

Dataset Content

PDF Documents: The dataset includes 2,677 PDF files, each representing a unique company document. These documents are derived from the Northwind dataset, which is commonly used for demonstrating database functionalities.

The document types are:

• Invoices: Detailed records of transactions between a buyer and a seller.
• Inventory Reports: Records of inventory levels, including items in stock and units sold.
• Purchase Orders: Requests made by a buyer to a seller to purchase products or services.
• Shipping Orders: Instructions for the delivery of goods to specified recipients.

Example Entries

Here are a few example entries from the CSV file:

Shipping Order:

• Order ID: 10718
• Shipping Details: "Ship Name: Königlich Essen, Ship Address: Maubelstr. 90, Ship City: ..."
• Word Count: 120

Invoice:

• Order ID: 10707
• Customer Details: "Customer ID: Arout, Order Date: 2017-10-16, Contact Name: Th..."
• Word Count: 66

Purchase Order:

• Order ID: 10892
• Order Details: "Order Date: 2018-02-17, Customer Name: Catherine Dewey, Products: Product ..."
• Word Count: 26

Applications

This dataset can be used for:

• Text Classification: Train models to classify documents into their respective categories.
• Information Extraction: Extract specific fields and details from the documents.
• Document Clustering: Group similar documents together based on their content.
• OCR and Text Mining: Improve OCR (Optical Character Recognition) models and text mining techniques using real-world data.

This statistic presents the share of internet users in the United States who feel comfortable about companies being able to purchase their personal data for online advertising purposes as of May 2018, sorted by age group. According to the findings, ** percent of respondents aging from 18 to 29 years stated to be very uncomfortable with the fact that companies are able to purchase their personal data for online advertising purposes. Only eight percent of them reported the opposite by being very comfortable with this.

The annual Small Business Procurement Scorecard is an assessment tool to (1) measure how well federal agencies reach their small business and socio-economic prime contracting and subcontracting goals, (2) provide accurate and transparent contracting data and (3) report agency-specific progress. The prime and subcontracting component goals include goals for small businesses, small businesses owned by women (WOSB), small disadvantaged businesses (SDB), service-disabled veteran-owned small businesses (SDVOSB), and small businesses located in Historically Underutilized Business Zones (HUBZones). Each federal agency has a different small business contracting goal, negotiated annually in consultation with SBA. SBA ensures that the sum total of all of the goals meets the 23 percent target established by law.

With 172,000 Businesses in Saudi Arabia , Techsalerator has access to the highest B2B count of Data/Business Data in the country.

Thanks to our unique tools and large data specialist team, we can select the ideal targeted dataset based on the unique elements such as sales volume of a company, the company's location, no. of employees etc...

Whether you are looking for an entire fill install, access to our API's or if you are just looking for a one-time targeted purchase, get in touch with our company and we will fulfill your international data need.

We cover all regions and cities in Saudi Arabia ( example) :

Hejaz Mecca Region Makkah Najd Riyadh Region Riyadh Eastern Arabia Eastern Region Dammam Southern Arabia 'Asir Region Abha Southern Arabia Jizan Region Jazan Hejaz Medina Region Madinah Najd Al-Qassim Region Buraidah Hejaz Tabuk Region Tabuk Najd Ha'il Region Ha'il Southern Arabia Najran Region Najran Badiah Al-Jawf Region Sakaka Hejaz Al-Bahah Region Al-Baha Badiah Northern Borders Region Arar

Use our Owler companies dataset, a sales intelligence and business information research company, to map your ecosystem, and find market trends and investment opportunities. Access a database of competitors, revenue, employees, and funding for any company. Depending on your needs, you may purchase the entire dataset or a customized subset. The Owler companies information dataset offers public information on all companies listed in Owler. The dataset includes all major data points: Company size Revenue News Key executives Location Website and more. Freshness configuration: monthly refreshes refresh rate of up to 8 million records a month

Procurement Analytics Market size was valued at USD 4.85 Billion in 2024 and is projected to reach USD 25.18 Billion by 2031, growing at a CAGR of 25.21% during the forecast period 2024-2031.

Global Procurement Analytics Market Drivers

Data-Driven Decision Making: Businesses are realizing the value of data-driven decision-making procedures in a variety of departments, including purchasing. With the help of insights from data analysis, procurement analytics helps businesses reduce risks, find cost-saving possibilities, streamline their purchasing procedures, and enhance overall procurement performance.

Growing Complexity and Globalization of Supply Chains: As supply chains becoming more intricate and international, businesses must deal with issues including risk reduction, supplier management, and regulatory compliance. Advanced capabilities to track supply chain interruptions, analyze supplier performance, and optimize sourcing strategies across several geographies and suppliers are provided by procurement analytics solutions.

Demand for Cost Reduction and Efficiency Improvement: Companies are under pressure to lower costs and boost operational efficiency in the cutthroat business world of today. Through spend analysis, supplier consolidation, contract optimization, and demand forecasting, procurement analytics helps businesses find cost-saving options that eventually result in bottom-line benefits.

📖 Dataset Description

This dataset provides an end-to-end view of vendor performance across multiple dimensions — purchases, sales, inventory, pricing, and invoices. It is designed for data analytics, visualization, and business intelligence projects, making it ideal for learners and professionals exploring procurement, vendor management, and supply chain optimization.

🔗 GitHub Project (Code + Power BI Dashboard): Vendor Performance Analysis[https://github.com/HARSH-MADHAVAN/Vendor-Performance-Analysis]

The dataset includes:

purchases.csv → Detailed vendor purchase transactions sales.csv → Sales performance data linked to vendors inventory.csv (begin & end) → Stock levels at different periods purchase_prices.csv → Historical vendor pricing vendor_invoice.csv → Invoice details for reconciliation vendor_sales_summary.csv → Aggregated vendor-wise sales insights

Use this dataset to practice:

SQL querying & data modeling Python analytics & preprocessing Power BI dashboarding & reporting

The generated dataset simulates marketing interaction data for 500 users, including a range of engagement metrics and user behavior features. Below is a detailed description of the columns in the dataset:

Columns: User_ID: A unique identifier for each user (e.g., '001', '002', etc.).

Likes: The number of likes the user has given to posts, normalized to a range of 0 to 1.

Shares: The number of times the user has shared posts, normalized to a range of 0 to 1.

Comments: The number of comments the user has made on posts, normalized to a range of 0 to 1.

Clicks: The number of times the user has clicked on posts, ads, or links, normalized to a range of 0 to 1.

Engagement_with_Ads: The level of interaction the user has had with advertisements, normalized to a range of 0 to 1.

Time_Spent_on_Platform: The amount of time the user spends on the platform (in minutes), normalized to a range of 0 to 1.

Purchase_History: A binary value indicating whether the user has made a purchase (1 for purchased, 0 for not purchased).

Text_Features: Text data that simulates user interactions with marketing-related content (e.g., posts, advertisements). The text has been transformed using TF-IDF (Term Frequency-Inverse Document Frequency) to extract important keywords.

Engagement_Level: A categorical value indicating the level of user engagement with the platform, including "High", "Medium", and "Low".

Purchase_Likelihood: A binary target variable that indicates the likelihood of a user making a purchase. It is encoded as:

1 (Likely) if the user is predicted to make a purchase. 0 (Unlikely) if the user is predicted to not make a purchase.

With 501,000 Businesses in the United Arab Emirates, Techsalerator has access to the highest B2B count of Data in the country.

Thanks to our unique tools and large data specialist team, we are able to select the ideal targeted dataset based on the unique elements such as sales volume of a company, the company's location, no. of employees etc...

Whether you are looking for an entire fill install, access to our API's or if you are just looking for a one-time targeted purchase, get in touch with our company and we will fulfill your international data need.

Graph and download economic data for Expensed Purchases of Software for Data Processing, Hosting, and Related Services, All Establishments, Employer Firms (EXPEPSEF518ALLEST) from 2005 to 2022 about software, employer firms, information, purchase, accounting, processed, establishments, expenditures, services, and USA.

Comprehensive dataset containing 37 verified Purchasing Department locations in United States with complete contact information, ratings, reviews, and location data.

Dataset

This dataset was created by Rahul Golder

Contents

Tailored Brands Worldwide Purchasing Company Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

United States Report On Business: PMI: Supplier Deliveries Index data was reported at 62.500 NA in Nov 2018. This records a decrease from the previous number of 63.800 NA for Oct 2018. United States Report On Business: PMI: Supplier Deliveries Index data is updated monthly, averaging 51.900 NA from Jan 1948 (Median) to Nov 2018, with 851 observations. The data reached an all-time high of 96.800 NA in Nov 1973 and a record low of 12.400 NA in Mar 1949. United States Report On Business: PMI: Supplier Deliveries Index data remains active status in CEIC and is reported by Institute for Supply Management. The data is categorized under Global Database’s United States – Table US.S001: Institute for Supply Management: Purchasing Manager Index.

American Atlantic Purchasing Company Llc Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.