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Blockchain, Bitcoin and The Art of Rolls Royce Repair

  • Todd Blaschka
  • March 16, 2018
  • blog, Fraud / Anti-Money Laundering, Machine Learning / AI
  • Blog >
  • Blockchain, Bitcoin and The Art of Rolls Royce Repair

Two questions always come up when I tell people that I work on blockchain. The first question is “Where do I get started with blockchain in my organization?” and that’s often followed by the second question, “Which technology should I build my blockchain on?” My answer involves the famous story of Mr. Rockefeller and his favorite car, a Rolls Royce Silver Ghost.

Mr. Rockefeller loved his Rolls Royce, so when it started making a strange noise, he called every expert auto mechanic, including those from the company. None of them could figure out what was wrong with the engine or how to fix it. Finally, he called a young mechanic who specialized in the specific model of Rolls Royce, Silver Ghost.

The mechanic stood next to the car and listened to the noise coming out of the engine for five minutes. He proceeded to take a hammer out his tool kit and tapped the engine once. Lo and behold – the noise was gone! Mr. Rockefeller was thrilled. He thanked the young mechanic and asked him what was owed for his service. The young mechanic smiled and said, “That will be a thousand dollars, sir.” Mr. Rockefeller was taken aback. “One thousand for five minutes of your time? That’s rather steep!” The young mechanic smiled and offered an explanation. “Oh, my time is worth just one dollar. The rest of the 999 dollars are for knowing where to tap the engine to fix the noise!”

This is an important lesson that applies to blockchain as well – find the right use case to get real business value out of it for your organization (“right spot on the engine to tap”) and implement that use case on the right technology (“the mechanic who knows where to tap”) that will provide the scale and functionality needed for your blockchain.

Picking the right use case for blockchain

Blockchain is essentially a digital shared ledger among multiple parties and the key value proposition of the technology is that it does not require the parties to trust each other. All of the transactions (called “blocks”) are added to the shared ledger and the ledger itself is replicated among all parties so that everyone has access to the shared, single version of truth, namely the blockchain.

There are two flavors of blockchain, public blockchain (such as bitcoin, a cryptocurrency based on blockchain technology) and private blockchain. Private blockchains are often called “permissioned blockchain”, because trading partners are invited to participate in it and each participant has a specific role. I recommend that most organizations start with permissioned blockchains, because they can control the participants and the scope for deployment and get business value sooner.

As you look at implementing a permissioned, private blockchain in your organization, I would ask you to find a use case that meets one or both of the following criteria. The first criterion is related to the value of each transaction. “Does this use case involve transactions with high value goods, assets or services that involve multiple parties?” Trading in valuable commodities such as diamonds or machines that cost thousands of dollars meets this criterion and is an excellent fit for blockchain. The second criterion is related to the frequency. “Does this use case involve a high volume of transactions with multiple parties?” International trade finance, where goods move from one country to another, has the high volume of transactions with multiple parties and therefore is an excellent fit for blockchain deployment.
Once you have picked your use case for blockchain that meets one or both of these criteria, it’s time to focus on picking the right technology.

Selecting the right graph database for your blockchain

Blockchains require three key attributes for the underlying technology used to store transactions or blocks. The first attribute is scalability. The technology powering blockchain must scale up to be able to create and maintain an ever growing number of blockchains, each involving a growing number of blocks. Consider a shipment of goods from China to United States tracked by blockchain. It involves the customer ordering the shipment, multiple freight forwarder agencies, custom clearing agents, various government agencies and a host of carriers who are involved in moving it from the factory in China, through all the ports and finally delivering it to the retail distribution center in United States. Each shipment creates hundreds of blocks tracking the goods, and there are thousands of shipments per month, creating an ever-growing mountain of data that must to be stored and updated in real-time. Many of you have experienced performance issues when trading with cryptocurrencies such as bitcoin, where it takes minutes, sometimes hours to confirm the sale. Lack of scalable technology infrastructure is partly to blame for the delay.

The second attribute for the blockchain technology is privacy for sensitive data. Each trading partner has a specific role (“customer”, “manufacturer”, “freight forwarder”, “custom clearing agent”, etc.) and should see their specific part of the blockchain transaction. Certain attributes such as order number, item number, quantity are shared with all participants and other attributes such as pricing or service level agreement (SLA) contracts are private and must be shared among smaller subset of participants. This is often the proverbial straw that will break the back of your camel, aka your blockchain.

Third, and the most important attribute for blockchain technology, is real-time analytics spanning multiple blocks or transactions. Business value delivered by blockchain comes from two areas. Reduction in manual reconciliation and administrative overhead is the first area, and most early implementations have focused on this aspect. The second area for the business value comes from better business insights by analyzing blockchain data and identifying patterns for fraud and inefficiency across the value chain. In the trade finance example explored earlier, the technology must support going across multiple blocks, tracking a specific shipment as it spans the globe, and be able to cross-over and look at other shipments that go through the same route or are being handled by the same custom clearing agent.

Choosing TigerGraph graph database to build your blockchain

TigerGraph platform is designed for massive parallel processing which makes it an excellent fit for blockchain deployments. With TigerGraph 2.0 release in March, we have added MultiGraph service which provides the ability to share public data among all participants, while restricting certain data segments to specific participants. Lastly, TigerGraph is the only graph database capable of providing real-time deep link analytics across multiple nodes or hops for massive datasets, making it the perfect foundation for your blockchain.

TigerGraph is used by the largest organizations in the world including Alipay, SoftBank, Wish and State Grid Corporation of China for real-time deep link analytics for massive data volumes with hundreds of billions of payments, locations, customers and partners.

By Gaurav Deshpande, VP of Marketing, TigerGraph

Want to learn more about TigerGraph and what it can do for your organization? Please take a test drive at our site and visit us at IBM Think 2018 at booth 764 in The Cloud and Data Campus.

Photo Credit: Bitcoin (Dan Kitwood/Getty Images), Rolls Royce (Malcolm Asquith)

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    Dr. Jay Yu

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    Dr. Jay Yu is the VP of Product and Innovation at TigerGraph, responsible for driving product strategy and roadmap, as well as fostering innovation in graph database engine and graph solutions. He is a proven hands-on full-stack innovator, strategic thinker, leader, and evangelist for new technology and product, with 25+ years of industry experience ranging from highly scalable distributed database engine company (Teradata), B2B e-commerce services startup, to consumer-facing financial applications company (Intuit). He received his PhD from the University of Wisconsin - Madison, where he specialized in large scale parallel database systems

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    Todd Blaschka is a veteran in the enterprise software industry. He is passionate about creating entirely new segments in data, analytics and AI, with the distinction of establishing graph analytics as a Gartner Top 10 Data & Analytics trend two years in a row. By fervently focusing on critical industry and customer challenges, the companies under Todd's leadership have delivered significant quantifiable results to the largest brands in the world through channel and solution sales approach. Prior to TigerGraph, Todd led go to market and customer experience functions at Clustrix (acquired by MariaDB), Dataguise and IBM.