Get ahead of the curve—learn about big data on the blockchain
Blockchain came to prominence as the disruptive technology that made cryptocurrencies work. Now, data pros are using blockchain technology for faster real-time analysis, better data security, and more accurate predictions. Blockchain Data Analytics For Dummies is your quick-start guide to harnessing the potential of blockchain.
Inside this book, technologists, executives, and data managers will find information and inspiration to adopt blockchain as a big data tool. Blockchain expert Michael G. Solomon shares his insight on what the blockchain is and how this new tech is poised to disrupt data. Set your organization on the cutting edge of analytics, before your competitors get there!
Learn how blockchain technologies work and how they can integrate with big data Discover the power and potential of blockchain analytics Establish data models and quickly mine for insights and results Create data visualizations from blockchain analysis Discover how blockchains are disrupting the data world with this exciting title in the trusted For Dummies line!
I gave this one a go out of curiosity, and while I’m not deep in the blockchain world (although could be analysing data on the blockchain in my future, I can see how Blockchain Data Analytics for Dummies would be really useful if you’re working in or around the space. The first few chapters were definitely the highlight for me—they broke down key concepts in a clear and digestible way, especially around how data is structured on the blockchain and how you can start making sense of it.
It does get pretty technical as it goes on, and I found myself skimming a few sections that felt more geared towards developers or specialists. That said, it’s a solid resource and good as a reference tool. It's not exactly a gripping read, but it will probably be a handy guide to keep on the shelf.
A nifty little introduction to the topic. The first 3rd of the book is all about the Ethereum network, creating your own Ethereum Virtual Machine, and extracting data from it. The last 2 thirds focuses pretty much solely on data analytics so I ended up skimming most of that part.