What is Commodity Data? Definition, Sources & Datasets to buy
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- FAQ
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- FAQ
What is Commodity Data?
Commodity data refers to information about raw materials or primary agricultural products that can be bought and sold, such as oil, gold, wheat, or coffee. It includes data on prices, supply and demand, production, inventories, and other relevant factors that impact the commodity markets. Commodity data is crucial for traders, investors, and businesses to make informed decisions and manage risks in these markets.
Examples of commodity data include information on the prices, supply and demand, production, and consumption of various raw materials such as oil, gas, metals, agricultural products, and energy. Commodity data is used by traders, investors, analysts, and researchers to make informed decisions in the commodities market. It helps them understand market trends, assess risks, and develop strategies.
Best Commodity Databases & Datasets
Here is our curated selection of top Commodity Data sources. We focus on key factors such as data reliability, accuracy, and flexibility to meet diverse use-case requirements. These datasets are provided by trusted providers known for delivering high-quality, up-to-date information.
Global Indices Data | Commodity Prices | Macroeconomic Indices | Currency Data | 40K Indices
Metal Pricing Data | Product Data | Commodity Data | Benchmarking | Historical Data | Region | Purchase Volume | Manufacturing Technology | CO₂ Data
Energy Data & Commodity Data—AdBlue/DEF prices for 44,000+ EU stations, plus Market, Oil & Gas, and Brand insights via API and datasets.
Financial Derivatives EoD Pricing | Options & Futures Pricing Data on Commodities
Tradefeeds Commodity Prices API
Commodity Prices API by Finnworlds
Phone Number Data API | Access 50M+ Verified Phone Numbers | Enhance Communication Strategies | Best Price Guarantee
Residential Real Estate Data | Assessor & Recorder of Deeds Data | Bulk + API | 158M Properties
Factori USA Consumer Graph Data | socio-demographic, location, interest and intent data | E-Commere |Mobile Apps | Online Services
Brain Sentiment Indicator - Currencies, Cryptocurrencies and Commodities
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Top Commodity Data Providers & Companies
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InfoTrie
InfoTrie: Global Data Intelligence Leader since 2012. Unleash insights from unstructured data. Alternative datasets on E-commerce, SEC Filings, B2B Data, Sentiment Analysis, Job Postings, Corporate & Financial Data, News & Social Media, iFeed API, DocuTrie & Custom Pipelines. Request a quote now!70000Asset Classes20+Languages5000+Active Users -
Cbonds
CoverageUSAUK+248VWe use the Cbonds API and are very satisfied with the data quality and the interface. Everything works smoothly, and the support has been reliable. We appreciate the service and look forward to continuing our cooperation.
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CrawlBee
CoverageUSAUK+247VI contacted CrawlBee's CEO, Ryan DeWitt through Datarade. Ryan is very flexible, friendly, and extremely helpful! he worked with me to get the mortgage data I need for my research project. The data is very thorough and accurate. I highly recommend CrawlBee as I truly had a very good experience!
Popular Use Cases for Commodity Data
Commodity Data is essential for a wide range of business applications, offering valuable insights and driving opportunities across industries. Below, we have highlighted the most significant use cases for Commodity Data.
Main Attributes of Commodity Data
Below, we outline the most popular attributes associated with this type of data—features that data buyers are actively seeking to meet their needs.
| Attribute | Type | Description | Action |
|---|---|---|---|
| Float | The latitude of a point on earth's surface. Commonly abbreviated as "lat". | View 7 datasets | |
| String | The Zone Improvement Plan (ZIP) code of an address. | View 6 datasets | |
| String | The name of a city. | View 5 datasets | |
| String | The last name (surname) of a contact. | View 5 datasets | |
| String | The name of a country. | View 5 datasets | |
| Float | The longitude of a point on earth's surface. Commonly abbreviated as "long". | View 5 datasets |
Frequently Asked Questions
How is the Quality of Commodity Data Maintained?
The quality of Commodity Data is ensured through rigorous validation processes, such as cross-referencing with reliable sources, monitoring accuracy rates, and filtering out inconsistencies. High-quality datasets often report match rates, regular updates, and adherence to industry standards.
How Frequently is Commodity Data Updated?
The update frequency for Commodity Data varies by provider and dataset. Some datasets are refreshed daily or weekly, while others update less frequently. When evaluating options, ensure you select a dataset with a frequency that suits your specific use case.
Is Commodity Data Secure?
The security of Commodity Data is prioritized through compliance with industry standards, including encryption, anonymization, and secure delivery methods like SFTP and APIs. At Datarade, we enforce strict policies, requiring all our providers to adhere to regulations such as GDPR, CCPA, and other relevant data protection standards.
How is Commodity Data Delivered?
Commodity Data can be delivered in formats such as CSV, JSON, XML, or via APIs, enabling seamless integration into your systems. Delivery frequencies range from real-time updates to scheduled intervals (daily, weekly, monthly, or on-demand). Choose datasets that align with your preferred delivery method and system compatibility for Commodity Data.
How Much Does Commodity Data Cost?
The cost of Commodity Data depends on factors like the datasets size, scope, update frequency, and customization level. Pricing models may include one-off purchases, monthly or yearly subscriptions, or usage-based fees. Many providers offer free samples, allowing you to evaluate the suitability of Commodity Data for your needs.
What Are Similar Data Types to Commodity Data?
Commodity Data is similar to other data types, such as Stock Market Data, Cryptocurrency Data, Alternative Data, ESG Data, and Credit Rating Data. These related categories are often used together for applications like Trading and Portfolio Optimization.
