When Blockchain Meets Big Data

Blockchain and Big Data are among the top emerging technologies tipped to revolutionize several industries, radically changing the way businesses and organizations are run.

In this day and age, data is money. Big data and blockchain technology can join forces to truly decentralize the global big data market.

With the world shifting its focus on digital technologies, big data is poised to take center stage in transforming a wide range of industries.

While Blockchain Technology is focused on recording validating data (data integrity), data science analyses data for actionable insight, making predictions from large amounts of data (prediction).

The convergence of big data and blockchain offers tremendous opportunities for organisations and consumers.

Why Big Data Needs Blockchain?

To understand how Big Data and blockchain could work together, it is essential to look at the challenges the data industry is currently facing. The two must work together to have a positive impact on the consumer.

Blockchain cannot work alone without some form of data, and Big Data cannot sort the large chunks of raw data. This dilemma brings the two technologies together for better data synchronization.

Big data is the compilation of massive datasets. Since data are usually extremely large and complex, it cannot be processed through traditional data processing systems.

Another big data challenge is security because traditional data is stored in centralized servers. This provides a fertile ground for hackers since they target the massive centralized data storage servers.

The Big Data industry can get handful on huge data, especially when stored in multiple servers. This consumers data at risk. Moreover, the more significant the data, the harder it can become to detect malicious or “contaminated” data from high-quality one.

The control of dirty data (or erroneous information) is one area where blockchain technology can positively impact the data science field. Moreover, blockchain restores the control of data to the individuals generating the data making it an uphill task for cybercriminals to access and manipulate data on a large scale.

Through decentralization blockchain validates data making it almost quite impossible to be manipulated due to the huge computing power that will be required.

Merging Big Data & Blockchain: A Creative Approach To Maximum Result!

Data science seeks to extract knowledge and insights from structured and unstructured data. This field encompasses statistics, data analysis, machine learning and other advanced methods used to understand and analyze actual processes using data.

Blockchain technology is focused on validating data while data big data involves making predictions from large amounts of data. Blockchain technology provides for the integrity of the ledger, however, not for the analysis.

This is how Big Data and accompanying analysis tools will come into play.

When Blockchain Meets Big Data

Credits: Unsplash

Data science usually focus on harnessing data for proper administration, blockchain ensures trust of data by maintaining a decentralized ledger. These data sets can be used for estimating behavioral patterns and market trends.

Big Data can have an additional layer of security if implemented on a decentralized network. The first layer of security can be attributed to the network architecture of the blockchain. Unlike the traditional methods, the information in the network is secure and cannot be duplicated.

Blockchain through its application of Smart Contracts can also perform transactions automatically.

However, one concern is that blockchain application in this regard will be very expensive to pursue. Its because data storage on a blockchain is expensive compared to traditional means.

Decentralizing Big Data

Below are a selected number of networks that are making use of some sophisticated developments to handle selected challenges the data industry currently face:

StreamrStreamr is a decentralized, scalable publish/subscribe network, designed for a lower-latency, real-time data from IoT sensors, machines, and other smart devices. Streamr’s mission is to build a decentralized infrastructure for real-time data, replacing centralized message brokers with a global peer-to-peer network.

ReBlocReBloc is a data marketplace for the real estate sector. The real estate sector currently suffers from a lack of transparency and trust in its data, hence trusted data is critical to a real estate sale. ReBloc uses a validation protocol to ensure accuracy and trustworthiness of data on its platform.

Endor ProtocolEndor Protocol is a blockchain-based AI toolset uses data pulled from online human-based sources and using artificial intelligence to generate crowd-based wisdom. It applies a discipline called “social physics” to generate answers to future-based questions.

StorJStorj is an open-source, decentralized file storage solution, similar to Dropbox, only that there is no central entity that manages the data. They use cryptography, sharding, and hash tables to help store files on a decentralized peer-to-peer network.

OmnilyticsOmnilytics combines blockchain with big data analytics. They use artificial intelligence and machine learning in conjunction with marketing, auditing, and trend forecasting. The entire system is fueled by the OMN tokens.

With more and more of these blockchain platforms looking to work on big data, the amount of quality big data and subsequent analytics are going to drastically impact the way companies do business all around the world.

Finishing Thoughts

We hope to see further progress in the partnerships of Big Data analytics and blockchain as developments in this space continue. As the technology matures and there are more innovations around it, more concrete use cases will be identified and explored to benefit Big Data management and data analysis.

As more data is collected in real-time it will be interesting to see how the blockchain will continue to revolutionise different industries and bring better data privacy.

Cover Image: Unsplash

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