Blockchain seems to be a trending topic these days, especially with the recent interest in data management and analytics services. From a data scientist’s perspective, blockchain is a stimulating source of high-quality data that can be used to tackle a wide range of data disputes using machine learning algorithms and statistical models.
One of the foremost challenges that the initial set of blockchain platforms faced is the inability to support analytics due to the storage of underlying transactional data in a key-value pair format. The querying of the current or historical state is only possible when the key is used. For example, data may be identified by a data finder stored as a key based on which blockchain data can be retrieved.
Introduction
Blockchain technology fundamentally refers to a database collection of information stored electronically on a computer system in a structured table format.
It is a decentralized system, which means no single entity will be solely responsible for controlling the data entry and its integrity. Blockchain technology offers a network of a distributed system, such that the same transaction can be shared over a wide network making it more secure via the design of network architecture. Additionally, blockchain technology is immutable, meaning it cannot be altered or changed once stored. The data or information remains the same if the network remains in the loop.
Blockchain Oriented Data Management and Analytics
The blockchain framework is designed to track every transaction in the distributed network to generate and manage huge volumes of data in the network architecture. Complete data in a blockchain is collected by clusters of computers that are not owned by any single entity and stored in a time-stamped series of immutable records. The data in these clusters are secured and bound to each other using cryptographic principles referred to as chains in the blockchain.
For instance, blockchain technology simplifies trusted information management, making it easier for government agencies to access critical public data while maintaining data integrity. The decentralized nature of blockchain allows data to be shared easily across the organizations, which can also control who can access what data and preserve its integrity.
Perks of Blockchain for Data Management
Real-time Data Analysis
The most effective way to stay protected from thefts and fraud in a data-driven industry is by running data analysis in real-time and monitoring changes as they happen. This kind of analysis is not yet in practice, but the emergence of AI and blockchain impacted its growth.
With its distributed and transparent nature, blockchain technology can notice any irregularities as they occur, allowing simultaneous collaborations on the same data sets and reducing areas of vulnerability in the data management life cycle.
Data Traceability
Traceability of data refers to how fast data can be traced out in terms of history, location, or application. Traceability is also used to manage, control and operate repeatedly used data from its origin to its consumption. Traceability is a recurrent challenge for food, manufacturing, and pharmaceutical industries as billions are lost due to theft and counterfeiting.
Blockchain technology plays a crucial role in reducing huge losses by enhancing traceability and giving tokens to each product as a unique identifier so that any information data assets can be stored securely. Blockchain operates in a linear path of succession enabling it to trace and follow through with the history of the chain of events securely, as required.
Data Quality
The data stored on various networks may be public or private, so the quality of data plays an important role in impacting analysis to make informed decisions about the business process. Blockchain technology inherently provides validation to the blocks of the data in the blockchain to give consistency to the data and ensure that inaccurate data does not enter the particular block. Additionally, cryptographic technology is also embedded in the block to provide more security to the data and ensure that data is of high quality.
Blockchain Supporting Analytics
Following the role of blockchain technology in enhancing data management, it has a huge potential to support analytics. One of the categories of data analytics that is poised to change the analytics industry in the future is predictive analytics. It is focused on making precise predictions on future outcomes with the help of historical data. However, the current scenario of predictive analytics is not accurate enough as the data is faulty or of bad quality, resulting in the hampering of future results. The biggest obstacle is in obtaining quality data from different sources and correlating them. Blockchain technology fills the gap in this analytics space because blockchain’s computational power is gained from multiple sources of connected systems, which is powerful enough to define the model to be analyzed based on a vast number of data sets. Data on the blockchain is a cryptographic distributed ledger accessible to identify key information about users and transactions. The cryptographic in blockchain refers to hiding the data in a secure format. Only the person who has access to data or a personalized key to access the data can use the data for a required purpose. With blockchain technology embedded in analytics, compliance departments can identify illicit activities, protect themselves from risk, and increase trust and transparency within the system, creating more cross-sell and up-sell business opportunities.
For instance, blockchain distributed application in the logistic industry enables end-to-end visibility and tracking for inbound and outbound logistics and a single source of information being exchanged in real-time. The distributed application is designed as an industry-agnostic business accelerator to support and track multiple tasks and make data-driven decisions based on extracted data.
Why Managing Data and Digital Assets is Important?
People who use public services are rightfully worried as criminals might gain access to government databases and steal or manipulate records, so protecting such critical data is very important. In 2018, for instance, many hackers tried to obtain personal details, social security numbers, fingerprints, employment history, and financial information for millions of public users who had been subject to a background check by the US government. Blockchains’ encryption method is not 100 percent safe, making it way more difficult to achieve similar breaches with blockchain technology.
As we are well aware, organizations are moving towards digital transformation, and all of the assets utilized in enterprises are increasingly being converted to digital formats. Digital assets are becoming increasingly important in education, banking, finance, healthcare, publishing, mining, etc. As a result, it becomes necessary to control them effectively. Digital assets such as data, applications, and systems are valuable for the industries mentioned above. The sensitivity of these assets varies greatly between industries. For example, there are sensitive healthcare data in hospitals, including patients’ information, and in financial institutions, digital transactions are the most valuable assets for them. In the last few years, the number of data breaches has doubled, and the number of attacks has increased significantly. As a result, it is critical to safeguard digital assets with a solid management approach.
Blockchain technology can assist in protecting sensitive data and reducing the likelihood of data breaches incidents occurring. It also ensures enhanced privacy and personal integrity. Blockchain technology could be a prominent solution for keeping digital assets safe and secure. It’s a decentralized and distributed online public ledger system for storing values and other valuables. Blockchain provides options for making data secure within the organizations’ validation networks and verifies the credibility of information. In the blockchain, data is saved with a hashtag, and it is difficult to change it. Blockchain is distributed among many validators, and it is incredibly difficult to tamper with data without being detected. Blockchain is a decentralized technology, and this means that data is replicated to each node in the system rather than being stored in a single, central location, which makes the destruction of data harder. In digital asset management, blockchain is useful where information needs to be referenced by numerous parties. Blockchain provides a complete history of audit trails that make it easier to determine modifications to an asset’s metadata. Additionally, blockchain is useful in the management of rights to digital assets. It allows the distribution of digital assets but disables copying, this provides an additional degree of protection against the unauthorized use of assets or information.
Conclusion
Blockchain technology is evolving with the technological advancement in artificial intelligence and machine learning domain. Though blockchain is commonly used in private and public industries, it is yet to reach widespread adoption. Its complexity and cumbersome nature make it difficult for users to trust the technology. Still, the cost of implementing blockchain makes it easier to implement it. The future potential of blockchain technology indicates that it must overcome challenges such as interoperability that will create a smooth communication and collaboration ability to share and access information across different blockchain networks without the need of an intermediary and financial resources.
For more on securing data and information security, visit Infosecurity Outlook.
