Today’s technological advancements are happening at an incredible rate. Big data and blockchain are leading forces in the tech revolution and are no longer considered emerging technologies. Organizations are being forced to change and adapt their business models as a result of this shift. It’s a common misconception that big data and blockchain function separately, in separate silos.
As a distributed ledger system, blockchain carefully records and verifies assets and business transactions over a network. However, the art of deriving significant conclusions from both unstructured and structured data is known as data science. The amount of data and its complexity are growing as these technologies advance. When data analytics and blockchain technology are combined, their combined strengths can be leveraged to create real power.
The use of blockchain technologies has significantly increased over the past ten years. The global blockchain market, estimated to be worth $2.89 billion in 2019, is projected to grow at an astounding compound annual growth rate of 62.7% to reach $137.29 billion by 2027, according to a study. The combination of data science and blockchain technology is expected to increase its market value even more.
What precisely is blockchain analytics, then?
The market for cryptocurrencies is expected to expand at a compound annual growth rate (CAGR) of 12.8% from 2021 to 2030, from its 2020 valuation of $1.49 billion. The process of looking through, recognizing, classifying, modelling, and visually representing data on a blockchain is known as blockchain analytics. To obtain useful information about the players in the cryptocurrency market, blockchain data analysis is done.
Blockchain data analytics entails examining a sequence of chronologically ordered data blocks. Through the examination, classification, and tracking of blockchain transactions, users can use blockchain data analysis tools to gain important insights and evaluate risks. Due to its broad analytical capabilities, blockchain data analytics stands out as one of the most exciting applications in data science.
By offering total transparency into unauthorized transactions, this technology also gives law enforcement and regulatory agencies the ability to track and identify illicit activities. Individuals and organizations can make better decisions when they have more visibility into trends and investments.
Let’s examine the potential connections between blockchain and the field of data analytics.
Comprehending Blockchain Technology
When Bitcoin, the first cryptocurrency, was developed, blockchain technology began to gain traction. Because of its popularity, a plethora of other cryptocurrencies that make use of blockchain technology have been developed. This innovation, which promises a new era of increased certainty and security in transactions, is frequently compared to the revolutionary impact of double-entry accounting in the business world.
Fundamentally, a blockchain is a distributed ledger that is safe from manipulation, transparent, and available to everyone. It acts as a trustworthy log of financial transactions.
There are two main types of blockchain: public and private. A closed network with only authorized users being able to read and write data is known as a private blockchain. A public blockchain, on the other hand, is accessible to anybody with an internet connection and enables all linked nodes to view data and transactions without requiring any additional authorization. The majority of cryptocurrencies are public blockchains, which provide unfettered access to transaction data.
What is Data Analytics?
By carefully examining data to find trends and patterns, data analytics helps businesses make wise decisions. It analyses both structured and unstructured data using cutting-edge methods, such as machine learning, to extract insightful knowledge.
Data is what propels organizational development. This data is mined, arranged, and intelligently analyzed using a variety of business apps. Data science improves customer service and overall experience in many industries, including healthcare and travel.
Integrating Data Science and Blockchain
In their own right, blockchain technology and data science are central to data. Combining these technologies adds a new level of functionality to data handling while satisfying a number of important criteria:
Blockchain technology makes data science output security more practical because of its strong network architecture. This guarantees the security of the data produced by data science procedures.
Additionally, blockchain offers a large, structured dataset that is prepared for further analysis. Cost-saving options are also provided by the combination of these technologies, particularly in the long-term data analysis and storage.
Research into the nexus between data science and blockchain is highly desirable. The emphasis on data that these two technologies share is what unites them. Blockchain is excellent at capturing and verifying data, guaranteeing its accuracy. As for data science, it is excellent at drawing significant conclusions from data to support decision-making and problem-solving.
In order to communicate with data segments, both technologies use algorithms. To put it simply, data science holds the key to unlocking predictive insights, while blockchain protects data integrity.
Among the advantages of how blockchain will improve data science are:
Enabling Data Traceability
The peer-to-peer network structure of blockchain enables improved data traceability. Another peer can examine the complete process from start to finish if there are any questions about the methodology employed by one account. This guarantees a thorough comprehension of how outcomes were attained.
Enabling Instantaneous Analysis
Blockchain technology makes real-time data analysis—a typically difficult task—more manageable. Companies are able to effectively detect any irregularities at an early stage by analyzing data as it happens. Moreover, blockchain enables concurrent work on the same dataset by numerous users, akin to the functionality of a shared spreadsheet. This feature improves collaborative data management by enabling real-time modifications and assessments by various users.
Ensures Data Accuracy
At the point of entry, blockchain data, which is stored on both private and public nodes, is subjected to stringent scrutiny and cross-verification. In order to guarantee that only correct data is added to the blockchain, this procedure serves as the first stage of data verification. This built-in characteristic of blockchain technology is essential to preserving data accuracy across the system.
Facilitates Easy and Smooth Data Sharing
Any organization’s seamless operation depends on the efficient and smooth flow of data. Conventional paper-based data management is difficult to maintain in addition to being laborious. Data flow and access are revolutionized in this way by blockchain technology. Multiple users can interact with the same data at once because it makes data viewing, transferring, and real-time access easier. Within-organization collaboration and data sharing are made much easier by this feature.
Enhances the Integrity of Data
Organizations today place a great value on the veracity of their data. The current focus is on protecting and confirming data integrity, whereas previous decades were primarily concerned with increasing data storage capacities—a challenge that was largely overcome by 2018. Since data frequently originates from multiple sources, it is prone to mistakes, inconsistencies, and duplications.
To address these issues, blockchain technology is developed, which guarantees data authenticity throughout the entire chain. The unchangeable security of this technology is a major factor in the increasing number of enterprises adopting it.
Every block on the blockchain requires multiple signatures on the records of the decentralized ledger, and data is cross-checked and verified. Access is only authorised in the event that every signature is precisely matched, greatly lowering the possibility of data breaches and hacking. The strong security feature of blockchain improves the system’s overall data integrity.
Encoded Transactions
Blockchain technology encrypts each transaction that is entered into the ledger using complex mathematical algorithms. By generating digital contracts that are irreversible and unchangeable, this encryption guarantees safe and reliable transactions between parties. These intricate algorithms are used in blockchain technology, which makes it a trustworthy medium for digital interactions by improving security and preserving the confidentiality and integrity of every transaction.
Data Lakes
Organizations frequently use data lakes to store enormous amounts of data in the field of data storage. Blockchain technology creatively uses the data’s original source to identify each piece of data and associates it with a distinct cryptographic key. The authenticity, quality, and correctness of the data are ensured by having the right key, which is connected to the data’s source. The utilization of cryptographic keys in blockchain technology not only safeguards data but also guarantees its authenticity and integrity, improving the overall dependability of information kept in corporate data lakes.
The need of Securing IoT Data
The overwhelming proliferation of devices and data being caused by the rapid expansion of the Internet of Things (IoT) is far greater than what can be monitored by humans. IDC research predicts that by 2025, IoT devices will produce an astounding 73.1 zettabytes of data. Big data technologies are excellent at handling and interpreting this enormous amount of data, but they are unable to offer the necessary security and trust.
Anyone can download the client software, view the ledger, and communicate with the blockchain on public blockchains. Because of this decentralization, the vast amount of data produced by IoT devices is not under the control of a single party. Lundqvist notes that because of this decentralization, it is very difficult for data records to be tampered with or corrupted.
Public blockchains, on the other hand, are mainly connected to cryptocurrencies and are intended to protect user privacy while treating every user equally. Lundqvist points out that although this is advantageous in certain situations, it turns into a drawback in business settings, such as IoT ecosystems. Control and privacy issues arise because public blockchains allow users to remain anonymous and are treated equally.
A lot of businesses find it unsettling to think that all participants will have unlimited access to the database. A new breed of private blockchains is arising in response. These blockchains are managed by a single body or authority, and access is only allowed after valid authentication.
Private blockchains still provide many of the distributed advantages of traditional blockchains, even though they sometimes resemble centralized networks. The control maintained in private blockchains improves privacy and lowers the possibility of illegal activity, which is frequently associated with cryptocurrencies and public blockchains.
Conclusion
The use of blockchain technology in data science represents a major advancement in data handling and security. As we’ve seen, blockchain offers data science a number of advantages, such as increased data integrity, smoother data sharing, and improved data accuracy.
Securing the enormous volumes of data produced by Internet of Things devices is especially dependent on the technology. Blockchain technology is expected to play an even more significant role in data science as it develops, opening up new avenues for data management, security, and analysis in a world that is becoming more interconnected.
