The Benefits And Challenges Of Applying Blockchain Technology To Big Data

Introduction

Blockchain technology’s popularity and wide application promote study in many practical and scientific fields. Blockchain is still in its infancy, yet it is already being praised as a game-changing technology that will finally end modern computing issues, including centralization, trust, identity theft, data ownership, and data-driven decision-making. 

The last several years have increased interest in using big data in many scientific and engineering fields. The interest in “big data” directly results from the exponential growth in global data traffic over the past decade. The healthcare, retail, logistics, manufacturing, media, and entertainment industries would all benefit greatly from the big data market’s predicted $229.4 billion value by 2025.

Big data has numerous potential uses and benefits. Still, it also presents many difficulties that must be overcome to ensure high-quality services, such as big data analytics, big data management, and big data privacy and security. Big data services and apps benefit significantly from blockchain’s decentralization and security features.

At the same time, both people and machines are creating more and more digital data, making the amount and types of digital data grow. Blockchain technology significantly contributes to the ongoing conversation on best storing, organizing, and analyzing Big Data. The solutions it proposes for issues like decentralized private data management, digital property resolution, IoT communication, and reforming governmental institutions will likely impact the future of Big Data significantly.

Unlock the potential of Applying Blockchain Technology to Big Data! Embrace the transformative synergy that enhances security and transparency in data management, revolutionizing information handling. Join us on an exciting exploration of this fusion in our informative blog.

The Role of Big Data in Modern Society

A brief description of Big data

The term “big data” refers to data sets that are both complex and very large. Big data can be analyzed to find confidential information that needs to be seen, such as market trends, unknown associations, patterns, customer interests, etc. Big data can also refer to gathering, cleaning, and analyzing massive volumes of data, enabling businesses to make sensible choices regarding their operations. Traditional apps that work with data can’t handle big data. 

There is too much information for the human brain to process. About 14.7 exabytes of data, or a billion gigabytes, was generated in 2008. Between 2014 and 2016, 90% of the data was compiled. Every click, share, like, and swipe creates massive data as consumers use their gadgets online.

The Impact of big data on Business

As the amount of data keeps growing, companies are looking for new ways to make the most of it and use the information it gives them to make decisions. Big data has a lot of effects on businesses, but one of the most important ones is that it makes them more dependent on the Internet and increases the amount of data they have to deal with. In a whitepaper, Seagate IDC said that by 2025, the world atmosphere will be 175ZB. 

Big data gives businesses the latest and most helpful information and insights, which they can use to make better and faster choices. The big data analytics tools also let companies improve their operations and efficiency, get a competitive edge, and find more ways to use big data.

With the help of big data, companies also want to make more money by giving better customer service. Most businesses’ main goal is to improve the customer experience. With the help of big data, you can also enhance your marketing plan, reduce expenses and make your business run more efficiently.

Big data has been helping companies in both social and economic ways over the past few decades. This is why some government agencies are implementing policies to encourage the growth of big data. 

Many sectors can benefit from big data, including banking, insurance, retail, manufacturing, logistics, the media and entertainment industry, and oil and gas.

The Impact of big data on the Workforce

Big data has a big effect on the business world and the way people work today. Today, many businesses use the Internet to connect with customers, generate sales, and improve productivity. As a result, positions requiring expertise in data science, big data engineering, and analysis are in high demand, as these professionals are the only ones capable of using massive amounts of data from the Internet. 

Many institutes and colleges offer online big data courses if you use the Internet or social media. This is because there is a rising need for data scientists and engineers who work with big data. Indeed’s research indicates that demand for data scientists will increase by 16 percent by 2028.

Due to a lack of data scientists and engineers, there is a big technology gap. Companies don’t have enough technical talent, so many organizations still have open jobs in analytics. In the future, there will be a lot of unstructured data and new software and technologies to use. There may also be a shortage of competent applicants at some companies.

Because of this, companies are using bots and RPAs more to automate tedious, repetitive jobs like sourcing, data entry, and data cleaning. 

The Social Impact of Big Data

Because the use of big data influences organizations, which in turn has an impact on the economy, which in turn affects society and the use of big data, it is like a circle that never ends. Big data is used to improve automation, security, and privacy in the production and healthcare industries. 

Big data can also predict the weather, natural disasters, urban and community planning, traffic management, logistics and machine efficiency, personal healthcare, customizable learning, autonomous vehicles, fraud detection, translation, smart homes, robots, etc.

The Synergy between Blockchain and Big Data

Here, we talk about why combining Bitcoin with big data makes sense.

 • Improving the security and privacy of big data: As the number of devices connected to the Internet grows daily, so does the amount of data saved in places like the cloud. This brings new problems, like data loss or threats from people who want to look around. Traditional security measures like firewalls can’t solve the problem of big data because organizations don’t have control over the data. After all, it’s not kept within the organization’s network perimeter. 

Using blockchain to store big data could help solve this problem. Unauthorized access to data on the blockchain network is difficult due to its encrypted and decentralized storage.

 • Making sure the data is correct: There is a chance that people will change the records in big data to make the predictions of big data analytics work in their favor. The immutability feature of the blockchain makes it nearly impossible to change the data stored in the blockchain network. 

If someone wants to change the data in the blockchain network, they have to change the data in at least half of the nodes in the blockchain network, which is nearly impossible in practice. Also, the immutability of the blockchain ensures that the data saved on the blockchain network is reliable.

• Fraud Prevention: Existing big data technologies detect fraudulent transactions by analyzing previous data patterns. Since this is the case, big data cannot solve the banking sector’s fraud problem. 

By storing big data in the blockchain, financial institutions can monitor every real-time transaction. This lets them check for possible fraudulent transactions as they happen. So, combining blockchain with big data can help financial institutions stop scams and keep their customers safe.

• Real-Time Data Analysis: Because the blockchain keeps track of every transaction, it is possible to analyze big data in real-time. Banks and other financial institutions can settle cross-border transactions, even if they involve a lot of money, in almost real-time thanks to the integration of big data analytics with blockchain. Furthermore, financial institutions can track data changes in real-time, allowing for immediate responses such as transaction blocking. 

• Better sharing of data: When blockchain and big data are used together, service providers can share data with other parties with less risk of data leakage. Also, if all the big data from different sources are saved in the blockchain, there won’t be any need to analyze the data more than once since each experiment is recorded in the blockchain. 

• Improving the quality of big data: Data scientists spend most of their time on data merging because different sources collect data differently. Using blockchain for data storage allows for better quality data as it is more organized and comprehensive. So, data scientists can use relevant data to make real-time estimates that are more accurate. 

• Streamlining Data Access: Using blockchain would make the life cycle of big data analytics easier by making it easier to access data online. If different organizational departments use the identical blockchain, authorized users can access secure, trusted data without going through several checks.

Benefits of Applying Blockchain Technology to Big Data

Combining big data and blockchain technology has a lot of benefits for many different types of businesses. By using the best parts of both technologies, organizations can improve security and transparency, improve the accuracy and reliability of data, lower costs and efficiency, and open up new possibilities for innovation. Let’s look more closely at each of these benefits:

1. Improved security and transparency

One of the most significant benefits of putting big data and blockchain together is improving security. Because of its distributed and unchangeable nature, blockchain technology offers a trustworthy and tamper-proof platform for storing and transferring information. Integrating big data with blockchain safeguards information from theft, alteration, and fraud. Blockchain’s cryptography makes it exceptionally challenging for hackers to steal information.

And because of blockchain’s transparency, multiple participants in the data ecosystem can access the same immutable record of transactions. With such transparency, everyone can see the same data, which lessens the potential for errors or manipulation. This allows businesses to earn the confidence of their customers and encourages teamwork, which is particularly useful in fields like healthcare and supply chain management, where accurate records are essential.

2. Increased Data Accuracy and Reliability

Integrating big data and blockchain can significantly improve data quality and trustworthiness. Big data analytics can help find trends, correlations, and anomalies because it can handle a lot of data from various sources. Organizations may develop a reliable and verifiable data source by combining this analytical power with blockchain’s distributed ledger design.

All members in a blockchain network must agree on the accuracy of the data stored in the network by consensus techniques, such as proof-of-work or proof-of-stake. This consensus mechanism works as a validation layer, ensuring the data is correct and accurate. Better decisions, fewer mistakes, and fewer risks are all possible when businesses have access to precise and reliable data.

3. Reduced Costs and Increased Efficiency

Integrating big data with blockchain can reduce costs and boost efficiency across a business. Traditional ways of storing and processing data often involve centralized infrastructures, which can be expensive to keep and have single points of failure. On the other hand, blockchain is a distributed ledger that can function without any central authority, thus minimizing the costs associated with such intermediaries.

Big data analytics can also help organizations find inefficiencies, improve processes, and make choices based on data. By using blockchain to store and share data, companies can make data management more accessible, reduce the amount of duplicate data, and make data more accessible. This streamlined method makes operations run more smoothly and lowers the costs of managing and maintaining data.

4. New Opportunities for Innovation

Big data and blockchain technology provide fresh opportunities for progress in many fields. The fact that a lot of data is available and that blockchain is secure and open offers opportunities for new business models, products, and services.

For example, combining big data and blockchain in healthcare can change how research occurs and how patients receive care. Secure access and sharing of anonymized patient data among institutions allow for more thorough investigation and individualized care. As in healthcare, combining big data analytics and blockchain allows real-time fraud detection, risk assessment, and safe financial transactions.

Smart contracts, a component of blockchain technology, can further automate and streamline commercial processes, eliminating the need for intermediaries while increasing efficiency. Combining big data and blockchain makes it possible to make decentralized marketplaces, digital identities, and new decentralized applications (DApps). This encourages creativity and shakes up traditional industries.

Industries Where Blockchain and Big Data Can Work Together

Supply Chain Management

There are several ways in which implementing blockchain technology into supply chain management can prove beneficial. The first is simplifying the process of checking for legal observance. Manufacturers and retailers must monitor their suppliers to ensure compliance with all laws and regulations, including those pertaining to the quality and safety of ingredients and the treatment of workers.

International companies may find it challenging to ensure compliance throughout the supply chain due to the wide variations in these requirements from one country to another.

Blockchain technology may be used to simplify this process by creating a public database of transactions and laws that anybody in the supply chain can see. This would let everyone in the supply chain see how suppliers follow the rules, so there would be no doubt about whether or not goods were made legally.

Healthcare 

The digital change in healthcare is already happening thanks to Big Data and Blockchain. Technology has the potential to resolve data problems as well. Many people and organizations contribute to preserving and managing healthcare data, which can be found in several places. This makes updating health information difficult and can negatively affect service quality and patient outcomes.

Blockchains, distributed, immutable, and nearly hack-proof ledgers, are the key to this problem’s resolution. By putting healthcare information on a blockchain, doctors and other health workers will find it easier to get up-to-date patient records, no matter where they were made. 

Another massive benefit of using blockchain in healthcare is that it saves money. Consulting company Accenture says that putting blockchain into the U.S. healthcare system could save $100 billion annually by 2025. This will reduce administrative costs, stop fraud, and help the business run better.

Notary

A notary is one of the most famous and most accessible uses for blockchain. Blockchain in a notary aims to safely timestamp the recording and storage of any document, electronic file, or transaction.

The information with the timestamps is shared on a network where everyone can see it, and no one person can change or delete it. Simply put, a notary uses blockchain to attest that an object or event existed and occurred at a given time and date.

The adoption of Blockchain-based networks in land registries, for instance, allows for the transparent and instantaneous recording of transactions. People are increasingly using blockchain-based notary services because they are safer than standard paper-based notarization.

Food Safety

The food supply chain is an excellent example of a structure that needs more openness and safety. This is especially true regarding ensuring that food is safe to eat.

The world’s food system can become more transparent, trustworthy, and safe using blockchain technology. It makes a permanent record of the source and storage conditions to achieve this. Also included: information on how each item got from the farm to your plate.

For instance, Walmart and IBM collaborated to track pork shipments to China using Blockchain technology to assure food safety. In a matter of seconds, rather than days or weeks, Walmart could track their pork back to the slaughterhouse thanks to this method. This was especially important when one of its sources got into trouble for selling tainted meat.

Intellectual property (IP)

There are a lot of problems in the IP industry right now, such as data breaches, piracy, fakes, and ownership conflicts. There are three ways blockchain can help solve these problems: with the help of digital identity, smart contracts, and Digital Rights Management (DRM).

Smart contracts ensure artists receive their earnings instantly upon sale. For instance, a Spotify subscriber pays $3.33 to listen to a song if they play it five times a month. Additionally, 0.5 cents goes to the artist; smart contracts can make this happen automatically.

Blockchain enables creators to specify the conditions under which their work may or may not be distributed or utilized commercially to aid in DRM. The blockchain would flag the transaction as illegitimate and prevent it from happening if someone tried to print an Instagram photo three times the amount they paid for.

The IP business can benefit from digital identity since it eliminates the need for fake profiles and content by verifying identities on the blockchain.

Blockchain and Big Data Projects and Platforms

Thanks to Blockchain developers, many decentralized data marketplaces are emerging. These platforms connect sellers and buyers of data through direct peer-to-peer interactions. 

With decentralized networks instead of central servers, these platforms offer services that restrict third parties from viewing the data they store. Users can also rent out their extra storage space on these Big Data Blockchain projects in trade for cash or cryptocurrency.

Many Blockchain platforms are trying to make money from the enormous need for businesses to understand better and use data for their goods and services while still controlling the data.

Here are some ways to use Blockchain and Big Data.

Omnilytics

Omnilytics is one of the first projects to combine Blockchain and Big Data. Omnilytics is a platform with artificial intelligence that collects numerous data types for analysis on one platform. This platform is helpful for data analysts, marketers, and retailers in understanding customer behaviors and market trends.

Omnilytics gathers information from many places, like retail websites and social media sites, to give readers a clear picture of how the market is doing.

Omnilytics plans to leverage Blockchain technology to establish a trustworthy market where customers may buy data analytics that other participants in the network have validated.

Storj

Storj, pronounced “storage,” is a distributed object storage platform built on blockchain that encrypts data from beginning to end. It’s an open-source initiative with the vision of creating the first global, decentralized cloud storage service. 

The first of Storj’s two offerings is Storj Labs, which lets people rent out extra storage space on their hard drives in exchange for STORJ tokens. The second is Storj Share, which enables developers to keep data on the Storj network using an open-source library called libstorj. 

Storj employs a Token-Curated Registry (TCR) mechanism to incentivize node maintenance. 

ReBloc

Landowners worldwide can benefit from ReBloc, a decentralized platform for managing real estate assets and registering land. 

ReBloc has a process to ensure its info is accurate and reliable. A smart contract is in charge of every data exchange. Before it is delivered to the person who requested it, it is checked against other data sets. 

After the data passes the validation process, the buyer can believe it no matter who gave it to them. The customer gets the info, and the vendor gets paid. The lack of transparency in the real estate market makes this tool very important.

Streamr wants to make a decentralized site where people can sell real-time data. 

Streamr’s primary objective is to provide a seamless experience for all participants in the ecosystem by facilitating the transfer of funds or data using existing Blockchain technology.

A method called “sharding” is used by Streamr. When a Blockchain record is broken up into smaller pieces (called “sharding”), each node on the network doesn’t have to carry the weight of the whole database. Thus, the network accelerates significantly.

Challenges and Limitations of Applying Blockchain Technology to Big Data

1) Security in Blockchain

The blockchain, a valid ledger, keeps track of digital transactions in many different areas, such as Internet of Things (IoT) apps (including data transactions from other devices), healthcare, and financial services. Through decentralization, the blockchain provides essential services such as data security and privacy. 

However, malicious users who try to fake the block information need about 50% more computing power. The name for this kind of attack is a 51% strike. Even though any user would need 51% of the computing resources to trick the blocks, the double spending attack is still possible. Smart contracts on the blockchain make the system more robust, so double-spend attacks can’t happen. 

The distributed nature of blockchains (which broadcasts each transaction across the network) will make fraudulent block transactions more challenging to execute. There are data security concerns with big data and analytics frameworks for handling big data, although blockchain and big data make a great pair. Blockchain is a promising candidate for big-data applications because it maintains a complete and consistent record of all past transactions. Sharing data while preserving privacy is crucial in healthcare, as big data manage large volumes of data from doctors, patients, clinicians, laboratories, and pharmaceutical companies. 

The researchers propose leveraging the protected blockchain framework’s decentralized data management to regulate access to massive data. In addition, the hyper ledger protects permissionless blockchains, which any user can join without verification. Hyperledger strengthens the permissionless blockchain by letting users who are part of a transaction use centralized systems. 

But as the chain gets longer and longer, there will be more and more records in the blockchain, making it very hard to process the data. The nodes are essential and resource-limited in blockchain applications like IoT. Still, key sharing, encryption, decryption, and digital signatures use more computing power because they use cryptographic functions in the blockchain. Miners, the nodes that do mining, are in charge of making new blocks and connecting them to the existing chain. This needs more computing power. Consequently, the cryptographic approaches or security measures utilized for better security in the blockchain system should not impose additional processing costs. 

The complexity of the data recorded in a blockchain grows exponentially daily, expanding the scope of possible blockchain applications. Therefore, it is essential to investigate blockchain data analytics so that blockchain can function more effectively even with complex data. It is also necessary to consider whether the blockchain is public or private, what security measures are in place, and how effectively it can manage data before combining it with other technologies like big data. 

2. Big Data Complexity 

The emergence of cloud computing and smart IoT applications has resulted in significant data gathering. Data management challenges such as inaccessible data, filthy or unclean data, and data privacy have all increased in prevalence along with the massive data growth in this information era. Data quality management has become more difficult since the emergence of big data. Companies should also check for the legitimacy of data sources, cleanliness, and data breach when dealing with larger, more complicated datasets. 

Moving all historical data into a digital format remains a significant challenge. Blockchain provides reassurance for data management in terms of security, but when adopting it, it must consider the difficulty of massive data management.

Typical analysis models and inefficient data processing techniques are to blame for many of the difficulties associated with big data. 

The computational complexity rises since representing and understanding massive data can be difficult. Heterogeneous sources in big data exhibit varying behaviors and patterns. The most important things about complex data are its type, organization, relationships, and wide range of quality. Data retrieval, topic analysis, text mining (sentiments and semantics extraction), and other big data mining operations will be more complex than with conventional data. Inefficient computational models will emerge from a lack of understanding of these features and domain-specific data processing methods. 

Designing the most abstract computational models requires a deep familiarity with the characteristics of massive data. Aside from its many sources and large size, the most important thing about big data is that it is constantly changing (real-time information). The processing systems for big data are complex enough to deal with the complexities of the data themselves. These systems were made to handle a lot of information, so they needed a lot of computing resources. There are many processing modes and computational requirements when describing the system’s complexity. 

By gaining a fundamental understanding of the system’s complexity, it is possible to boost the efficiency of massive data processing systems significantly.

It is essential to develop a robust framework while also considering the factors that affect the energy consumption of large data processing systems. The critical factors are job calculation precision, energy efficiency, power usage, data storage distribution, parallel processing, and system throughput. 

In addition, mobile networks have more significant opportunities to enhance their service quality using big data. Integrating big data with blockchain to better big data processing models requires protecting the data’s complexity. 

It is also essential to analyze the mapping between complexity and computation, energy consumption, and efficiency to outline efficient approaches to data sharing, trusted transactions, data access, intruder detection and heightened security via decentralized blockchains.

Conclusion

Security, transparency, privacy, quality, and traceability improvements are just a few of the many advantages of using blockchain technology with big data sets. To fully capitalize on the potential of blockchain technology in big data, however, there are some obstacles that need to be overcome. These obstacles include scalability, storage, computational overhead, regulatory compliance, and interoperability. As the technology grows and improves, it will be important to solve these problems if we want to see the changing power of blockchain in the big data field.

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