Humankind is creating 2.5 quintillion bytes of data daily, much of which is collected by reputed ai services offering companies looking to improve their businesses. But not every company uses that data to its full advantage
Which is why Zhang sees a future for his DxChain. The big data and machine learning network
The Blockchain’s Data Storage & Computational Limits
In a recent interview, Zhang suggested that so much data analysis today focuses on the question of “what” is happening rather than “why.” However, he believes moving beyond the “what” and into the “why” helps companies better understand their customers. He also believes that delving into the why enables better business decision-making when in data analysis.
Zhang also suggests that blockchain’s data storage and computational capabilities will fundamentally change the nature of the internet. And yet, as Zhang observes, no one specific blockchain has yet to solve the problems posed by big data storage and computation needs. Indeed, he points out that most blockchains only provide transaction-related computations and are unable to run more general level computations (as blockchains can only store small datasets in its ledger).
DxChain’s Chains-on-Chain Solution
Zhang asserts that DxChain’s unique capabilities can solve this problem. It’s structured to provide parallel computations, machine learning applications, and business intelligence support. As stated above, the secret sauce is DxChain’s system infrastructure, as it uses a chains-on-chain framework.
In particular, its master chain facilitates transaction-related operations while coordinating two side-chains as well (reserving one such sidechain to execute parallel computations and another for storage and support). By utilizing side-chains, DxChain dramatically increases its capacity for resolving data storage, computational blockchains, and privacy issues.
Using Hadoop With The Blockchain
Today, only a handful of large enterprises have the capacity to perform big data analysis. Most enterprises cannot afford to scale their hardware appropriately, let alone obtain the widespread consumer data needed for such analysis.
4 Interesting Applications
1) Expect DxChain to be exceptionally helpful in a Smart Cities environment, where large data sets are submitted for machine learning analysis.
2) Dxchain’s utility in machine learning analysis will even extend to generating business intelligence reports and guiding critical business decisions.
4) With DxChain, developers will also be able to build machine-learning
However, these applications just scratch the surface.
To learn more about DxChain, click on dxchain.com