| | December 201819CIOReviewEvery day, more than 2.5 quintillion bytes of data is being created worldwide with further prospects of this number increasing exponentially in the coming years. The current dynamics of a lot of modern corporate organizations is that they are running on an engine, which is fueled by data and offers the advantage of analytics in return--the big data engine. However, like any other thing in demand, big data too has its own limitations. Being prohibitively expensive, big data adoption today is also limited by the technical skills needed to implement it. Big Data Block (BDB) is changing this scenario by combining open source software connecting massive networks with decentralized nodes of a global blockchain network of computers in order to orchestrate large-scale data analytics tasks. BDB eliminates the complexities associated with big data processing through blockchain technology and spreads the computing burden across computers within BDB's ecosystem. Jason Cohen, CEO of BDB says, "We offer our technology at a reasonable price point to our customers, charging only when the customer is actually running something, unlike other providers who are offering the same service for a monthly subscription. This also eliminates the need for our customers to worry about scalability as the system can run any size job across its blockchain data network." BDB is leveraging the mining concept similar to the way users mine Bitcoin for essentially validating the network and getting paid in those coins in return. The company allows their data processing partners to load its system using a Docker container analogous to a mining instance on their devices. This makes them a node in BDB's data network. BDB's customers then can use the system for their analytics needs and pay for that usage and this revenue is split between BDB and these partners. Leveraging the decentralized model of the blockchain dramatically reduces the cost for the customers and increases data security. "We are providing a user-friendly, front-end interface, and associated backed data processing network for our customers that will eliminate any technical knowledge needed to launch a big data initiative. BDB eliminates the overhead and cost of either hosting your own big data environment or using a cloud solution. BDB can keep costs low because we don't have that overhead either as we are leveraging the scale of the blockchain for this and rewarding those that provide their computers a share in the revenue." says Jason Cohen. BDB's platform also facilitates a knowledge exchange system allowing customers to take their analytics or data on the platform and share it with the community either for a fee or for free, collaborating or helping other customers in the process. Elaborating on the brilliance of the platform Jason Cohen cites a case study with a company in the motion capture space that deals with motion capture information for commercial and retail products. They are currently integrating with BDB's platform, and have decided to leverage their 20 years worth of motion data to do advanced historical data analysis. The doctors can use the platform to create an ecosystem around this data enabling them and their community to use or augment this data and do their own analysis, and share it with the community through the platform.Growing rapidly with its open-source and proprietary technologies, BDB plans to launch additional components for the platform within four to six months. The BDB team is currently working on the ability to provide persistent data lake functionality for their customers as a constant repository of their information. With a pipeline of projects in the development stage, BDB is also contemplating on introducing data streaming capability for its customers in the future. 20 MOST PROMISING BLOCKCHAIN TECHNOLOGY SOLUTION PROVIDERS - 2018Big Data BlockThe Democratization of Big Data with BlockchainJason CohenWe are providing a user-friendly, front-end interface, and associated backed data processing network for our customers that will eliminate any technical knowledge needed to launch a big data initiative
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