Blockchain has dominated headlines as the hottest area of technology development over the last couple of years. There are countless ways that forward-thinking organizations can utilize the technology to enhance business. Currently, there are several blockchain use cases in almost every industry. However, the leading areas where blockchain has made tremendous progress are-startups and deep-pocket corporations.
As things stand today, seems to be out of reach for small and medium-sized businesses (SMEs). The digital divide keeps widening by the day. But, the good news is that some blockchain projects are emerging with a promise to democratize the technology for SMEs. Moreover, the same approach could benefit Big Data and analytics.
So, how does influence data science? There are numerous benefits of combining with big data, and this guide will highlight them. We also look at some real-world of and big .
Blockchain: A highly demanded skill nowadays
As the number of blockchain projects continues to grow, the demand for blockchain developers has skyrocketed over the last few years. Even freelancing platforms like Upwork have reported that is one of the most demanded skills. Professionals in other areas like law or IT also have a competitive advantage if they have blockchain skills.
What is data science?
involves extracting knowledge and insights from both structured and unstructured data. This scientific field encompasses , machine learning, statistics, and other advanced methodologies in analyzing actual processes using data. Data is today considered the new oil. Consequently, tech giants like Google, Facebook, Amazon, and Apple are in control of enormous loads of data.
is helpful in analyzing huge sets of data and drawing useful insights. Some common of data science include internet engine protocols, recommender services, and digital advertisement. In fact, data analytics is a key component of data science that has found relevance in the healthcare industry. It helps to track patient treatment and equipment flow. In the travel industry, it enhances consumer experience.
are similarly in high demand. Every organization wants to get more insight into their data and solve problems. When considering big data, the need for data scientists is even more pronounced. The advanced aspect of data science deals with extremely huge amounts of data that you cannot handle with traditional data processing methods.
How blockchain can help big data
If big data refers to the quantity, then could be the quality. While big data analytics focuses on getting accurate predictions from large amounts of data, helps to validate the data. has introduced a whole new way of managing and operating with data. Organizations no longer have to look at data from a centralized perspective. The decentralized nature of means that users can manage data right from the edge of their devices. Moreover, integrates with a myriad of technologies like ( ), the Internet of Things (IoT), and cloud solutions.
Now, validated data that comes through is structured and complete. The platform is also immutable, so nobody can alter the data. Additionally, ensures data integrity by ascertaining the origin of data through its linked chains.
How blockchain influences data science
There are at least five practical benefits of in big data analytics. They include:
Enabling predictive analysis
Blockchain data can be analyzed to get valuable insights into the behaviors and trends that can be used to predict future outcomes. Moreover, provides structured data generated from individuals or individual devices. apply predictive analysis on large sets of data to determine the outcome of social events with good accuracy. Examples include predicting dynamic prices, customer lifetime value, customer preference, and churn rates in a business.
The distributed nature of and the massive computational power available through the network allow data scientists to execute extensive predictive analysis even for small organizations.
Real-time data analysis
Blockchain enables real-time cross-border transactions, just like digital payment systems. Many fintech innovators and banks are now exploring the potential of in providing real-time settlement of huge amounts of money irrespective of geographical limitations. Similarly, organizations that require real-time analysis of data can benefit from blockchain-enabled systems. Banks can monitor the changes in data in real-time and make quick decisions like blocking suspicious transactions or tracking abnormal activities.
Ensuring data integrity/trust
Blockchain ensures that the data recorded is trustworthy by taking it through a verification process. It also enhances transparency since all the activities and transactions that happen on the blockchain network can be traced back. Lenovo successfully demonstrated this blockchain use case by detecting fraudulent forms and documents. The PC giant used to certify physical documents that were secured with digital . They use computers to process digital . However, the authenticity of the documents is verified through a blockchain record. More often, data trust is achieved when the details of the document origin and interactions can be traced.
Preventing malicious activities
Since blockchain uses consensus algorithm to validate transactions, a single unit cannot pose a threat to the entire network. Any that begins to behave abnormally can be identified and expunged from the network. is a distributed network, so it is impossible for a single entity to hold adequate computing power to alter the validation criterion and execute malicious transactions. To make any alteration to blockchain rules, the majority of the must be enjoined to reach a consensus.
Blockchain technology is surely revolutionizing the field of data science. While the technology is still in its infancy stages, the wider public adoption will make the ecosystem more robust. Developers will continue improving on the building blocks that are already in motion. There is no doubt that will take data science to a whole new level. However, the challenge is that we don’t have many blockchain systems on an industrial scale. The future is promising, though, as efforts to create as a service (BaaS) intensify.