What is common between blockchain and big data/data science? A few things that immediately hit our mind are that both are amongst the top emerging technologies. Both have the potential to revolutionize the way businesses are running, and both offer promising employment opportunities.
Many of us think that these are disparate and independent technologies with different sets of pros and cons and separate paths. While data science is a relatively established technology, blockchain is in the nascent stage. To compare them better, let’s understand more about each of them.
What is Blockchain?
Blockchain is a distributed ledger consisting of multiple nodes connected without a central server. This ledger is spread across a range of computers across the globe and run by anyone with an Internet connection. True to its name, blockchain technology revolves around the concept of a series of interconnected blocks that form a chain.
Applications of Blockchain
Primarily used in Bitcoin, blockchain is no more restricted to its original cryptocurrency application. The technology is being used in digital wallets and micropayments. Besides the financial sector, the technology can be used in Smart Contracts that perform listed tasks without human involvement.
Blockchain can also be used to store patients’ data in the healthcare industry securely. It’s also considered as a possible means to combat election fraud at the ballot box. Additionally, the technology can help carry out secure, personal transactions between two parties in the private consumer world. Read more about the applications of Blockchain.
Benefits of Blockchain
Characterized by decentralization, the blockchain transactions are carried out with mutual user consensus and offer safety, speed, and transparency. The digital signature feature used by the technology enables fraud-free transactions preventing the attempts to change or corrupt data. Each transaction is encrypted and consists of a link to the old transaction using a hashing method. The technology is programmable and automatically triggers systematic actions, events, or payments on the specified criteria. Read more about the advantages of blockchain in everyday life.
Challenges faced by Blockchain
As already mentioned, blockchain technology is in its early stage and is yet to mature. The technology can currently process a maximum of 7 to 20 transactions per second as compared to the capacity of traditional transaction networks, which can process thousands of transactions per second. Most of the blockchains are incapable of communicating with networks of other blockchain-based systems, and businesses also face challenges to integrate them with their legacy systems.
Lack of universal standards across different blockchain networks also poses a significant challenge. The current blockchain mechanism needs substantial computational power to work, and efforts are in progress to reduce this energy consumption. Also, despite the soaring demand for blockchain professionals, there is an acute shortage of blockchain experts.
What is Data Science?
With the advent of big data, organizations can store massive information. Data science enables businesses to make better decisions and predictions by discovering hidden data patterns from raw data. It’s all about deriving data insights from the historical trends that reveal multiple data angles, which might be unknown earlier.
Your guide to understanding the technology of trust
Data Science Applications
Data science is used for building predictive causal analytics models, such as to ascertain the probability of customers making timely future credit card payments or loan repayments. The technology can be used in prescriptive analytics where you can build models with the intelligence to make decisions to modify it with dynamic parameters, such as a self-driven car.
Besides this, data science can be used to build predictive models using machine learning, such as fraud detection, and explore pattern discovery, such as identifying an ideal tower location for a network provider for delivering optimal signal length. Read about data science applications.
Benefits of Data Science
Data science helps businesses enhance efficiency by taking faster and better decisions and earn higher profits. It improves the quality of data and information and helps deliver superior services and products using customer trends and likings. In healthcare, technology enables taking life-saving decisions such as detecting early-stage tumours. The technology offers highly paid career opportunities across various domains. Read on why data science is important.
Challenges faced by Data Science
Data used in making decisions can contain personal or sensitive data. Any data leakage can result in privacy threats and data issues. As the data is used to make critical decisions, any unproven data can lead to unexpected results, affecting crucial decision-making.
Difference between Blockchain vs. Data Science
Now that we have in-depth information about blockchain and data science, it’s apparent that these are two disparate technologies with different goals. While data science aims to facilitate data analysis for actionable insights and better decision making, blockchain focuses on recording and validating data. Both of these technologies use algorithms to achieve what they are intended to do.
To summarise, data science enables data prediction, while blockchain ensures data integrity. Therefore, if we are comparing them, it’s like comparing apples to oranges. However, if we use them in tandem, they can provide precious insights.
How organizations can reap the combined benefits of Blockchain and Data Science?
The following five aspects will throw more light on the impeccable combination of these two innovative technologies:
- Data Security – The ‘Decentralization’ of blockchain makes it difficult for hackers to attack sensitive information as it will require compromising all the nodes, which is virtually impossible. Further, blockchain automatically expels any node that behaves suspiciously, making the system secure.
- Data Integrity – Blockchain ensures data integrity with its encryption and stringent verification process. Further, it provides much-needed transparency through transaction traceability.
- Real-time Data Analysis – While blockchain offers real-time transactions, data science provides in-depth data analysis. These two technologies can be combined to deliver real-time data analysis that can revolutionize many industries and streamline business processes.
- Prediction Making – Data science’s capability can be utilized to analyze blockchain data to derive valuable data insights and hidden trends.
- Data Sharing – By using a blockchain network to store the data from data studies, project teams can prevent utilizing already used data or avoid repeating data analysis that’s already been conducted earlier. The technology can help send the information securely without the need to duplicate data cleansing.
Must Read: Data Science vs Data Analytics
The Winning Combination
With their share of benefits and challenges, blockchain and data science can prove to be a powerful combination to manage data quantity with quality efficiently. More innovations and maturity of blockchain technology will facilitate the exploration of more use cases, including data science.
On the other hand, data science can help blockchain with its low storage cost. It will be interesting to see how these technologies evolve to address current challenges and showcase their potential to transform data management and usage.
If you’re interested to become a blockchain developer and build smart contracts and chaincodes, checkout IIIT-B & upGrad’s PG Certification in Blockchain Technology.