http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/
This is a dataset that requires a lot of preprocessing with amazing EDA insights for a company. A dataset consisting of sales and profit data sorted by market segment and country/region.
Tips for pre-processing: 1. Check for column names and find error there itself!! 2. Remove '$' sign and '-' from all columns where they are present 3. Change datatype from objects to int after the above two. 4. Challenge: Try removing " , " (comma) from all numerical numbers. 5. Try plotting sales and profit with respect to timeline
Success.ai offers a cutting-edge solution for businesses and organizations seeking Company Financial Data on private and public companies. Our comprehensive database is meticulously crafted to provide verified profiles, including contact details for financial decision-makers such as CFOs, financial analysts, corporate treasurers, and other key stakeholders. This robust dataset is continuously updated and validated using AI technology to ensure accuracy and relevance, empowering businesses to make informed decisions and optimize their financial strategies.
Key Features of Success.ai's Company Financial Data:
Global Coverage: Access data from over 70 million businesses worldwide, including public and private companies across all major industries and regions. Our datasets span 250+ countries, offering extensive reach for your financial analysis and market research.
Detailed Financial Profiles: Gain insights into company financials, including revenue, profit margins, funding rounds, and operational costs. Profiles are enriched with key contact details, including work emails, phone numbers, and physical addresses, ensuring direct access to decision-makers.
Industry-Specific Data: Tailored datasets for sectors such as financial services, manufacturing, technology, healthcare, and energy, among others. Each dataset is customized to meet the unique needs of industry professionals and analysts.
Real-Time Accuracy: With continuous updates powered by AI-driven validation, our financial data maintains a 99% accuracy rate, ensuring you have access to the most reliable and up-to-date information available.
Compliance and Security: All data is collected and processed in strict adherence to global compliance standards, including GDPR, ensuring ethical and lawful usage.
Why Choose Success.ai for Company Financial Data?
Best Price Guarantee: We pride ourselves on offering the most competitive pricing in the industry, ensuring you receive unparalleled value for comprehensive financial data.
AI-Validated Accuracy: Our advanced AI algorithms meticulously verify every data point to ensure precision and reliability, helping you avoid costly errors in your financial decision-making.
Customized Data Solutions: Whether you need data for a specific region, industry, or type of business, we tailor our datasets to align perfectly with your requirements.
Scalable Data Access: From small startups to global enterprises, our platform caters to businesses of all sizes, delivering scalable solutions to suit your operational needs.
Comprehensive Use Cases for Financial Data:
Leverage our detailed financial profiles to create accurate budgets, forecasts, and strategic plans. Gain insights into competitors’ financial health and market positions to make data-driven decisions.
Access key financial details and contact information to streamline your M&A processes. Identify potential acquisition targets or partners with verified profiles and financial data.
Evaluate the financial performance of public and private companies for informed investment decisions. Use our data to identify growth opportunities and assess risk factors.
Enhance your sales outreach by targeting CFOs, financial analysts, and other decision-makers with verified contact details. Utilize accurate email and phone data to increase conversion rates.
Understand market trends and financial benchmarks with our industry-specific datasets. Use the data for competitive analysis, benchmarking, and identifying market gaps.
APIs to Power Your Financial Strategies:
Enrichment API: Integrate real-time updates into your systems with our Enrichment API. Keep your financial data accurate and current to drive dynamic decision-making and maintain a competitive edge.
Lead Generation API: Supercharge your lead generation efforts with access to verified contact details for key financial decision-makers. Perfect for personalized outreach and targeted campaigns.
Tailored Solutions for Industry Professionals:
Financial Services Firms: Gain detailed insights into revenue streams, funding rounds, and operational costs for competitor analysis and client acquisition.
Corporate Finance Teams: Enhance decision-making with precise data on industry trends and benchmarks.
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Investment Firms: Identify potential investment opportunities with verified data on financial performance and market positioning.
What Sets Success.ai Apart?
Extensive Database: Access detailed financial data for 70M+ companies worldwide, including small businesses, startups, and large corporations.
Ethical Practices: Our data collection and processing methods are fully comp...
http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/
This is a compiled datasets comprising of data from various companies' 10-K annual reports and balance sheets. The data is a longitudinal or panel data, from year 2009-2022(/23) and also consists of a few bankrupt companies to help for investigating factors. The names of the companies are given according to their Stocks. Companies divided into specific categories.
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Company fundamentals data provides the user with a company's current financial health and when combined historically, the financial 'life-story' of the company.
Our Financial API provides access to a vast collection of historical financial statements for over 50,000+ companies listed on major exchanges. With this powerful tool, you can easily retrieve balance sheets, income statements, and cash flow statements for any company in our extensive database. Stay informed about the financial health of various organizations and make data-driven decisions with confidence. Our API is designed to deliver accurate and up-to-date financial information, enabling you to gain valuable insights and streamline your analysis process. Experience the convenience and reliability of our company financial API today.
https://www.aiceltech.com/termshttps://www.aiceltech.com/terms
Korean Companies’ Financial Data provides important information to analyze a company’s financial status and performance. This data includes financial indicators such as revenue, expenses, assets, and liabilities. Collected from corporate financial reports and stock market data, it helps investors evaluate financial health and discover investment opportunities, essential for valuing Korean companies.
Every public company publishes a financial report to declare the financial activities and position of a business. This financial statement contains many tables to present the information. We classify these tables into predefined categories, such as below.
1) Income Statements 2) Balance Sheets 3) Cash Flows 4) Notes 5) Others
Datasets: Within the given dataset you will find 5 folders with the above category names. Every folder contains .html files with respective tabular data.
Expecting the grouping of documents in such a way that the files appear distinguished as per their category. The categories can only be used as a benchmark for evaluation later.
Data extracted: The data has been taken from the Publically available Hexaware Technologies financial annual reports. You can find here on link https://hexaware.com/investors/
Thank you for your Patience, Enjoy the dataset and Explore and learn more. Peace out✌️
https://www.lseg.com/en/policies/website-disclaimerhttps://www.lseg.com/en/policies/website-disclaimer
Browse LSEG's US Company Filings Database, and find a range of filings content and history including annual reports, municipal bonds, and more.
The Financial Statements of Holding Companies (FR Y-9 Reports) collects standardized financial statements from domestic holding companies (HCs). This is pursuant to the Bank Holding Company Act of 1956, as amended (BHC Act), and the Home Owners Loan Act (HOLA). The FR Y-9C is used to identify emerging financial risks and monitor the safety and soundness of HC operations. HCs file the FR Y-9C and FR Y-9LP quarterly, the FR Y-9SP semiannually, the FR Y-9ES annually, and the FR Y-9CS on a schedule that is determined when this supplement is used.
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Access historical and point-in-time financial statements, ratios, multiples, and press releases, with LSEG's S&P Compustat Database.
The number of shares outstanding, shown on a company’s balance sheet under the heading “capital stock” is used to calculate key metrics including market capitalization figures, earnings per share (EPS) and share stakes for regulatory reporting levels. The Share Outstanding service consists of two datasets, Official Shares Outstanding and Daily-Adjusted Shares Outstanding.
Official Shares Outstanding Providing official figures sourced directly from local exchanges or company sources, as soon as they are published. The frequency of official updates varies from market to market. Updates can also range from daily to annually.
Adjusted Share Outstanding When corporate actions occur prior to the release of official updates, the number of shares outstanding can be impacted drastically. Use the adjusted shares outstanding dataset to provide the figures for events including:
Bonus
Bonus rights
Buyback
Capital Reduction
Consolidation
Conversion
Demerger
Divestment
Entitlement
Redemption
Rights
Sub-division
Once the official figures have been released by the exchange, then receive reverted figures. The Worldwide Shares Outstanding service provides up-to-date figures from over 100 countries worldwide enabling companies to efficiently calculate figures to comply with exchange regulations or portfolio holding levels.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
Dataset Card for Financial Fraud Labeled Dataset
Dataset Details
This dataset collects financial filings from various companies submitted to the U.S. Securities and Exchange Commission (SEC). The dataset consists of 85 companies involved in fraudulent cases and an equal number of companies not involved in fraudulent activities. The Fillings column includes information such as the company's MD&A, and financial statement over the years the company stated on the SEC… See the full description on the dataset page: https://huggingface.co/datasets/amitkedia/Financial-Fraud-Dataset.
Comprehensive database of over 100,000 financial filings from 8,000+ European companies
Custommade Historical Financial Data For 230M Companies Worldwide: - Data from 2017, 2018, 2019, 2020 & 2021 - Includes turnover, employee size. - Custommade based on geographical location, turnover range, employee range and industry type - Standardized database for all countries
Make data work for you. With unbeatable data, skilled data experts and smart technology, we help businesses to unlock the power of international data.
https://www.lseg.com/en/policies/website-disclaimerhttps://www.lseg.com/en/policies/website-disclaimer
Browse LSEG's Officers & Directors, discover our range of data, indices & benchmarks. Our Data Catalogue offers unrivalled data and delivery mechanisms.
Our comprehensive and advanced database is completed with all the information you need, with up to >1.5 million company financial records at your disposal. This allows you to easily perform company search on company profile and company directory, with 99% coverage in Malaysia.
Our database also contains company profiles on private limited or limited companies globally, including information such as shareholders and financial accounts can be accessed instantly.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides a comprehensive view of a company’s financial and operational performance over the period from 2019 to 2023. It includes key metrics such as revenue, net profit, total comprehensive income, total assets, total equity, customer base, and indicators for return on equity (ROE) and return on assets (ROA). Additionally, the dataset contains a dummy variable to indicate the occurrence of a significant cyber incident in 2022. Data Fields:Year: The fiscal year for the reported data.Revenue (million GBP): Total income generated from sales and other operations, measured in millions of GBP.Net Profit (million GBP): The profit after all expenses, taxes, and costs, reported in millions of GBP.Total Comprehensive Income (million GBP): A measure of company performance that includes net income and other comprehensive income, reported in millions of GBP.Total Assets (million GBP): The total value of everything the company owns, reported in millions of GBP.Total Equity (million GBP): The shareholders' equity, representing the residual interest in the assets of the company after deducting liabilities, reported in millions of GBP.Customer Base (millions): The number of customers the company serves, measured in millions.ROE (%): Return on Equity, calculated as (Net Profit / Total Equity) * 100, and expressed as a percentage.ROA (%): Return on Assets, calculated as (Net Profit / Total Assets) * 100, and expressed as a percentage.CyberIncident: A binary variable (0 or 1) indicating the occurrence of a cyber incident in the corresponding year, with ‘1’ indicating an incident and ‘0’ indicating none.Key Insights:Revenue Growth: The company has shown significant growth in revenue, particularly from 2021 onwards, reflecting a strong upward trend in business performance.Profitability: After a challenging period in 2019 and 2020, the company achieved positive net profit starting in 2021, with substantial growth by 2023.Operational Efficiency: The ROE and ROA values demonstrate an improving trend in the company’s efficiency in utilizing equity and assets to generate profits.Customer Expansion: The customer base has expanded rapidly, tripling from 10 million in 2019 to 35 million in 2023, indicating successful market penetration and customer acquisition strategies.Cyber Incident Impact: A notable cyber incident occurred in 2022, which may have influenced financial and operational metrics during that period.Potential Uses:This dataset is valuable for financial analysts, researchers, and business strategists interested in understanding the financial trajectory, operational efficiency, and market growth of a company over a five-year period. It also provides insights into the impact of cyber incidents on company performance.
https://brightdata.com/licensehttps://brightdata.com/license
Use our Stock prices dataset to access comprehensive financial and corporate data, including company profiles, stock prices, market capitalization, revenue, and key performance metrics. This dataset is tailored for financial analysts, investors, and researchers to analyze market trends and evaluate company performance.
Popular use cases include investment research, competitor benchmarking, and trend forecasting. Leverage this dataset to make informed financial decisions, identify growth opportunities, and gain a deeper understanding of the business landscape. The dataset includes all major data points: company name, company ID, summary, stock ticker, earnings date, closing price, previous close, opening price, and much more.
https://choosealicense.com/licenses/other/https://choosealicense.com/licenses/other/
Dataset Information
This dataset includes quarterly earnings reports for various US stocks.
Instruments Included
7000+ US Stocks
Dataset Columns
symbol: The stock ticker or financial instrument identifier associated with the data. date: The end date of the fiscal period for which the financial data is reported. reported_date: The actual date on which the company reported its earnings or financial results. reported_eps: The earnings per share (EPS) that the… See the full description on the dataset page: https://huggingface.co/datasets/paperswithbacktest/Stocks-Quarterly-Earnings.
https://www.lseg.com/en/policies/website-disclaimerhttps://www.lseg.com/en/policies/website-disclaimer
Browse LSEG's I/B/E/S Estimates, discover our range of data, indices & benchmarks. Our Data Catalogue offers unrivalled data and delivery mechanisms.
http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/
This is a dataset that requires a lot of preprocessing with amazing EDA insights for a company. A dataset consisting of sales and profit data sorted by market segment and country/region.
Tips for pre-processing: 1. Check for column names and find error there itself!! 2. Remove '$' sign and '-' from all columns where they are present 3. Change datatype from objects to int after the above two. 4. Challenge: Try removing " , " (comma) from all numerical numbers. 5. Try plotting sales and profit with respect to timeline