03 Feb Blockchain vs Data Analytics: What’s the Difference?
When it comes to the world of business, there are two words that are constantly tossed around: blockchain and data analytics. But what do these terms actually mean? And what are the differences between them?
In this blog post, we will explore the world of blockchain technology and data analytics and discuss what makes them both so important for data science businesses today.
Understanding Blockchain technology
Blockchains are a peer-to-peer distributed ledger to record transactions, track and build trust among parties and provide an underlying mechanism to share data.
Traditionally used in cryptocurrencies, Blockchain today can serve a wider range of functions than its original application.
Instead, it has applications in practically all industries such as logistics and identity management. Because blockchains are a centralized technology, they can be negotiated by consensus among the participants and provide total transparency.
A lack of professional expertise in blockchain and data science is leading to increasing demand for blockchain development specialists within the blockchain network, bringing in salaries that were unheard of before.
What are some differences between blockchain and data analytics?
There are a few key differences between blockchain and data analytics. First, blockchain is decentralized, while data analytics is centralized. Second, blockchain is transparent and immutable, while data analytics can be manipulated.
Finally, blockchain relies on cryptography to ensure security, while data analytics relies on passwords and access control.
Blockchain is better suited for tracking digital assets, such as data or intellectual property. Data analytics is better suited for analyzing physical assets, such as factories or stores.
Blockchain is transparent and immutable, while data analytics can be manipulated.
Blockchain is permissionless, meaning anyone can use it, while data analytics requires permission from an authority figure to access it.
Data science and data integrity all encompass using unstructured data to uncover hidden data patterns through extensive predictive data analysis tasks and clear data science aims. Some people consider blockchain just another aspect of in depth data analysis and something that exists within the data science space, but the differences are clear.
Blockchain technology and data science can both help complete extensive predictive analysis tasks and assist data scientists to conduct real time data analysis.
Data analytics relies on pre-existing datasets, while blockchain creates its own dataset as it goes along.
A huge part of understanding open data science, data integrity, blockchain data is understanding the ins and outs of big data and data analytics, and there is nothing more important to Incus than providing a strong foundation and understanding of data analytics and moving you from raw data confusion to clarity.
IF YOU’RE A DATA NOVICE OR JUST LOOKING TO GET THE MOST OUT OF YOUR EXISTING DATA MANAGEMENT, GET INTO CONTACT WITH THEM ABOUT THEIR WORKSHOP OR SPECIFIC SERVICES THAT ARE TAILOR MADE FOR YOUR ORGANIZATION.
But the workshop is just the beginning. Consulting with Incus Services as part of your data improvement drive can make all the difference between being a leading organization or falling behind the competition.
If you want to find out more about data dictionaries, data governance, or even work on a data dictionary project, reach out and make the best of your business objectives by checking out the Three Most Powerful Analytics Techniques.
Incus Services can work closely with your organization to help your data talk to you and offer key insights. It is our objective to provide businesses with the machine learning and artificial intelligence strategies that they need to succeed.
Aren’t you ready to take your business to the next level? Why wait another moment to lead the finance sector through technology and digital transformation?