- Data Categories
Agriculture Data 
B2B Data 
Biometric Data 
Company Data 
Conservation Data 
Demographic Data 
Economic Data 
Environmental Data 
Geospatial Data 
Healthcare Data 
Individual Data 
Industry-Specific Data 
Internet of Things (IoT) Data 
Legal and IP Data 
People and Employment Data 
Political Data 
Psychology Data 
Real Estate Data 
Retail & Commerce Data 
Social Data 
Space Exploration Data 
Sports & Entertainment Data 
Web Data
- Data Categories
- Agriculture Data
- B2B Data
- Biometric Data
- Company Data
- Conservation Data
- Demographic Data
- Economic Data
- Environmental Data
- Geospatial Data
- Healthcare Data
- Individual Data
- Industry-Specific Data
- Internet of Things (IoT) Data
- Legal and IP Data
- People and Employment Data
- Political Data
- Psychology Data
- Real Estate Data
- Retail & Commerce Data
- Social Data
- Space Exploration Data
- Sports & Entertainment Data
- Web Data
Blockchain Technology
How is External Data Used in Blockchain Technology?
Blockchain technology stores data in blocks that are chained together and given a unique public ID. The content of the block is private but this ID is visible to anyone, which ensures that the data is secure: since the blocks are chained together, timestamped, reference all other nodes, and simultaneously recorded in many different locations around the globe, the chain becomes more secure as it grows.
As such, blockchain technology is used for all kinds of sensitive data. Most commonly, this means financial transactions—especially cryptocurrency—but may also include employee contracts, supply chain data, inventories, and medical records. Proponents of blockchain technology also argue that voting could be done quickly and securely with blockchain.
As blockchain technology matures, it becomes more secure, prompting more and more industries to adopt it. Governments have begun using this technology to plan innovation zones, aerospace engineers to design refueling stations, cybersecurity firms to revolutionize their entire industry, and on and on. The use cases follow the data itself in increasing exponentially.
How are Machine Learning Models Used in Blockchain Technology?
Many examples of machine learning programs based on or using blockchain technology exist. Smart contracts, for example, store contract data on a blockchain but then an ML program works to detect bugs or inconsistencies or to alert employees to attempted unauthorized access to contract data.
There are also machine learning programs that are based on blockchain technology. For example, automated navigation, or various parts of smart cities ecosystems, like smart meters. Essentially, the decentralized nature of the blockchain allows different sensors or network segments to record and communicate data; automated systems then take action based on that data.
Which Companies Lead the Way in Building Advanced Analytics and Machine Learning Products in this Field?
Bitcoin
The first and, arguably, still the greatest application of blockchain technology. Bitcoin is the preeminent cryptocurrency and is nearly synonymous with blockchain technology itself. Anyone, anywhere in the world, can start using and trading in Bitcoin: all that’s needed is internet access.
Tenderly
One of the most trusted smart contract companies, Tenderly guides its clients in the development, analysis, and management of company contracts. Users from a wide range of industries build custom contracts and enjoy Tenderly’s error tracking and intruder detection services.
IBM Food Trust
IBM applies blockchain technology to food distribution. Every stage on the food supply chain is recorded: from farmer to processor to distributor to trucker to retailer to home. With this, IBM and its partners ensure food is safe and fresh.
Connected Datasets
PipeCandy eCommerce Leads & Insights for Fulfillment
PipeCandy eCommerce Leads & Insights for Fulfillment tracks company data and company shipping details: shipping volume, which companies they use to ship products, whether they ship internationally or not, and so on. You can find company leads easily with this dataset with filter capabilities.
Wikiroutes Transit Data
Wikiroutes Transit Data provides public transport information—routes, stop points, and more—via crowd-sourcing. The data is constantly updated and can be easily converted and integrated into your own software system.
Wikiroute’s Transit Data is used by individuals, private companies, and government agencies of all types and sizes.
TrackStar Predictive Credit Technology
TrackStar’s Predictive Credit Technology uses fifteen years of financial dispute data to create predictive models of future borrowing potential. With this data and AI technology, your bank or other lending company can mitigate the risk of fraud, improve existing customer relations, and reduce your operating costs.