Find the right data set
Trusted by visionaries
Altadata team provides a unique perspective on information with a blend of business and technical expertise to solve complex problems. EPO Platform provides results beyond traditional regression analysis in a fraction of the time. It truly puts information and insight into the hands of the business.
Senior Manager Strategy & Operations at RBC
EPO benchmarking technology provided rich insights, while we optimized our 90 country portfolio of brands and categories. The study was subsequently shared with the Coca-Cola Company HQ.
Group Strategy and Business Planning Director at The Coca-Cola Company Eurasia & Africa
We have been working with the team behind Altadata, implementing EPO Platform. At Garanti BBVA excellence in customer service is our top priority. We use EPO's advanced analytical capabilities to exceed service level targets with optimal staffing.
Executive Vice President at Garanti BBVA
From day one of our partnership, the insight and expertise offered by the Altadata team has been invaluable. Taking the time to thoroughly understand our business’s unique needs, they delivered a data and insights solution which not only addresses our current challenges, but also sets us up for the future.
Chairman at Cundari Marketing
EPO Analytics Platform and Altadata services helped our sales management to determine how to use available resources more effectively. With the EPO, it is easier to allocate/reallocate resources and follow up performance results.
Former Country President at Novartis Turkey
EPO's Peer Benchmarking methodology has added great value to our target setting capabilities. We simply moved from comparing our portfolios and branches against averages to comparing against peers, both for performance reviews and target setting. EPO’s goal-driven interface enables us to transparently test new targeting models with speed and ease.
Nazan Somer Ozelgin
EVP at Yapi Kredi Bank
Frequently Asked Questions
Questions & Answers
What is Finance Data?
There is a vast amount of finance data that comes in all sorts of variety in the world. Organizations, exchanges, regulators, traders, arbitrators, market makers and sovereign governments all generate and collect finance data. We can classify Finance into Debt markets and Equity markets. These are further classified as public markets or private markets. Private market data are data regarding private transactions (sometimes also called Over the Counter or OTC transactions) and typically not publicly disclosed. Trade data and data on prices of goods, services, and commodities (such as price of a barrel of oil) are not considered as finance data at ALTADATA. Further, the data is segmented by geography of the trade or location of the exchange.
Finance Data at ALTADATA is data on a substantial subset of the US public equity markets. That is companies listed on NYSE or NASDAQ. All US registered public companies are required to submit certain filings about their operations, financial health, and provide data required to ensure fair practices. ALTADATA collects company data from the Securities and Exchange Commission (SEC) filings. There are more than 5000 publicly registered companies in the US exchanges. ALTADATA provides data on only the Russell 3000 companies. (Same as Russell 1000 and Russell 2000 companies combined.) These largest companies (approximately 3000 in count) comprise of more than 98% of the valuation of the total US market.
Who uses Finance Data? What are some use cases?
Finance data can be used for many different purposes. An economist may want to estimate trends in economic activity in a certain sector, say banking. Traders may want to benchmark companies based on fundamental data in their financial statements. Examples of this could be financial leverage and operating leverage. Financial analysts may use other ratios such as operating margin, price to earnings, debt to equity, and dividend payout to recommendations. Financial analysts can use growth data (revenue growth, earnings growth, etc.) to extrapolate future trends. Sector analysis can reveal clues into lifestyle changes and future trends.
What are typical Financial Data attributes?
Fundamental data from Balance Sheets, Income Statements, and Cash Flow Statements are the primary basis of our financial data. From daily closing stock prices and SEC reported data a plethora of financial indicators and factors can be calculated. In time dimension, year-over-year and quarter-over-quarter changes are reported. In terms of KPIs, many ratios are pre-calculated. And in terms of markets, price changes and volatility can indicate investor sentiment.
The primary data attributes are:
- Operating Expense
- SG&A Expense
- R&D Expense
- Operating income
- Interest Expense
- Tax provisions
- Net income
- Earnings per share
- Dividend Payout
- Cash and Equivalents
- Current Assets
- Total Assets
- Total Debt
- Total Liabilities
- Shareholder Equity
- Periodic Cash Flow in Operations
- Periodic Cash Flow in Financing Activities
- Periodic Cash Flow in Investment Activities
- Free Cash Flow
- Basic Shares
- Diluted Shares
- Closing Price
- Trade Volume
- Market Cap
- Market Sector
And many ratios and growth factors based on the above data.
How is Finance Data typically collected?
We collect and curate financial statement data from SEC data and report it in a standardized form. The advantage of this is so that companies can be compared based on features of their reported operations.
ALTADATA also collects and reports price and composition movements for certain market sectors and market indices in the US. These are S&P500 index, SPY, and SPDR ("Spider") sector ETFs for:
- Basic Materials
- Health Care
- Consumer Staples
- Consumer Discretionary
- Real Estate
What are the common challenges when buying Finance Data?
Financial Market Data is available from many sources. The primary questions are frequency, recency, reliability, coverage, and last but not least, price.
ALTADATA's objective is to provide reliable curated financial data with daily or weekly updates at a very reasonable price. Our frequency is typically daily or weekly. Our financial data is not suitable for day-trading or volatility trading. Our data is geared towards understanding fundamentals and long-term trends.