For some time now, it’s becoming apparent that data scientists not only have to toy around with data, but also convert it into a resource for predicting a company’s performance. The roles of data managers can oscillate anywhere from automating operations, nourishing customer relationships, or communicating a company’s objectives. This results in a language that stakeholders and other interested parties can understand.
Despite a lot of promising efforts, software and other programs employed by data scientists still don’t help much in achieving the lofty goals companies have. There is still a need for a powerful and affordable software to optimize data collection and organization. Blockchain is one of the most recent developments that many data stakeholders believe could fill that gap.
Blockchain displays some marvelous qualities that endear it to data personnel. Why do you think people like Nick Szabo and Vitalik Buterin fell in love with it and massively contributed towards its development?
For instance, the incorruptible nature of this distributed ledger means data can remain valid for eternity without anyone manipulating it. Since the chain is distributed, data interoperability between different entities could be made possible.
Let’s take a quick look at some of the barriers in big data and how blockchain can solve them.
Some Big Data Barriers and
How Blockchain Can Solve Them
Lack of Multiple Data Sources
The latent significance of big data lies in their efforts to access data from several platforms with ease. This makes data collection and comparison easy and less costly. Additionally, deeper insights can only be obtained when a company has plenty of data sources to cross-reference against.
Cloud-based services like ClicData are able to link data centers to various locations where data is stored. Unfortunately, these services are costly and it’s still hard to tell if the data is valid, genuine, or manipulated.
With blockchain in place, various firms can share data easily thanks to the open-source nature of the technology. Blockchain interoperability means companies can cross-reference data and see what they are doing wrong or right. It’s through this sort of comparison that a firm can step up its game.
UPS, one of the renowned shipping companies joined hands with BiTA (Blockchain in Tracking Alliance) in order to keep everything transparent among the parties involved in the chain. According to the company, interoperability and collaboration are essential in facilitating global trade. FedEx also joined BiTA this year with an aim of launching a blockchain that will help them solve customer issues for better feedback.
Protecting Intellectual Property
In September 2016, Yahoo was in hot soup for divulging their users’ data to the public –including the most private details we struggle to keep away from data sniffers. Data breach also happened to Target and Equifax, making most corporations explore alternative secure storage methods.
Yahoo, Equifax, and Target are not the only copmanies looking for a reliable storage system. Eastman Kodak is also trying to keep itself relevant in the smartphone generation by employing blockchain to its data storage methods. Through the encrypted and immutable ledger, photographers will now be able to store photos on the blockchain and even license them on the chain to prevent other individuals from claiming ownership rights.
Any firm can have a hard time accessing data especially if it exists in different locations and those in charge of it are not in good communication. Big data exists merely to mine, coordinate, and combine data for actionable insight. Unfortunately, if a company has branches in different parts of the world, it would be an expensive endeavor to have all those sets of data on one shelf.
Blockchain is ubiquitous. All the nodes on the network, whether from Africa, Asia, Europe, or America can access all the data at the same time without the need to put up costly infrastructure.
Walmart is one of the companies in the supply chain that is looking to make data accessible to their clients. Through the distributed technology, the company will help customers track the goods they use all the way to their production point. The technology will help the company restructure its restocking process.
Data monetization is still a huge setback for most companies. With huge volumes of data to segment, it becomes hard for a company to assign a portion of their data to another firm. With blockchain, data sets can be stored with a specific signature or hash function thereby making it easy to assign only that part to another party.
Data monetization is advantageous and is expected to make data more universal to any person or organization in the coming years. Data commercializing will also help property owners get compensated fairly than before.
Wibson is an example of a company that is working on helping individuals and companies market their data directly to buyers and advertisers. Through their system, small businesses will now be able to locate already engaged clients with surgical precision. This should save any company from spending a lot on traditional methods that don’t work effectively.
Inefficient Data Monitoring
Data monitoring can be simple for smaller companies and the consequences can be less severe if data conflicts occur. However, for companies in industries such as airlines, the effects can be adverse if some data. For instance, consider a conflict of flight arrivals and departures.
To avoid accidents from happening, a Wall Street Journal article indicated that British Airways is leveraging the blockchain’s unchangeable history to monitor and minimize conflicting flight info emanating from the airline’s website, gate monitors, and flight apps.
The Bottom Line
Inarguably, data is a strategic asset that every company capitalizes on. Virtually all business decisions revolve around information analysis. With a formidable team of data analytics specialists and blockchain gurus, any company is bound to remain relevant in their marketplaces for a long time. Blockchain may be a nascent technology but it could surely be the key to solving problems inherent in big data.