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The Main Challenges Involved In Monetizing Your Data

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The Main Challenges Involved In Monetizing Your Data


When businesses get every aspect of it right, data monetization can be hugely profitable for them.

However, when they don’t, the process becomes problematic and punishing. Overcoming the challenges of data monetization must be a priority for businesses looking to use information as a revenue generator.

The idea of using data for revenue generation has been around for some time. Several businesses monetize data with varying degrees of success in various sectors too. It is necessary to know that data monetization is anything but an easy process to implement successfully. Several processes—data collection, analysis, processing and management—need to be handled competently to overcome the various challenges of data monetization. Here are some of the problems that need to be resolved for your business to monetize data effectively:

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Lack of Infrastructure

Businesses need to have dedicated hardware and software infrastructure for data management before they can make monetization strategies. One of the main roadblocks in data monetization is that businesses are not equipped to provide Information-as-a-Service (IaaS) to buyers. This, coupled with the lack of flexibility and scalability required for self-service subscription and access and spikes in data volume, prevent businesses from capturing and monetizing data. Therefore, the first and foremost challenge of data monetization is to invest time and money in building a tried-and-tested framework for the purpose.

Lack of Confidence

Businesses may be overly cautious regarding data collection and exploitation. This trepidation regarding the process stems from fear of losing the value of collected data—rendering the long and arduous exercise of setting up infrastructure, employing personnel for extracting, refining, organizing, and storing data in a bid to sell it to buyers in exchange for money. The value of data is lost when businesses fail to protect the integrity of collected data and maximize its economic value by updating it continuously. Negligence causes data to lose its value, even if it is high-value information such as consumer purchase intent-related data, smart city data, or sentiment analysis-based data. The value of data can also decrease if specific weaknesses and incompetency in collection cause the data quality to be poor, automatically reducing its commercial appeal for advertisers and other types of buyers.

In today’s digitized ecosystem, data is the ultimate weapon. If you wish to monetize data, your business needs to conduct research to understand the true market value of all the information you generate. Once that is out of the way and other challenges of data monetization are addressed, your business will reap the rewards of intelligent data management.        



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TECHNOLOGY

How Blockchain and Big Data Can Work Together

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How Blockchain and Big Data Can Work Together


Big data and blockchain work well together by providing more security and integrity. 

One is transforming data management while the other is changing the nature of transactions altogether. Could they create an even more significant impact on the industries by binding together – big data for blockchain or blockchain for big data?.

Big data technologies first came into the picture at the dawn of this millennium to meet the computational needs of large datasets in the Internet-era. Proprietary applications like BigTable by Google and ZooKeeper at Yahoo showcased the potential of big data. However, the potential could only be tapped into after open-source projects such as the Hadoop File System (HDFS) and Hadoop MapReduce hit the market. Since then, big data has snowballed to transform how companies manage their data in the 21st century. Satoshi Nakamoto, an anonymous mystic individual, introduced the world to blockchain in 2008. It was developed in an attempt to solve the problem of double spending in transactions by eliminating the need for a third party in financial transactions. Blockchain also gave the world its first digital cryptocurrency – the bitcoin. Since then, the concept of blockchain has rapidly evolved to provide robust solutions to problems persisting in a wide array of industries. Now that both big data and blockchain are established as effective tools to tackle issues in different domains, we look forward to – possible methods of integrating both big data and blockchain to deliver even better solutions to specific problems, or as we’ve called it in this article, blockchain for big data and big data for blockchain.

How Big Data Works With Blockchain

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A lot of governments have had trouble with the anonymity clause of blockchain. Despite being favored for its security and infallibility, blockchains are turned down for not being able to track stakeholders in transactions, thus being a preferred choice for illegal trade. Big data applications can help make blockchains trackable by managing structured datasets of wallet addresses and their owner details. This kind of infrastructure can convince governments to adopt blockchain as a platform for transactions that demand speed, safety, reliability, and traceability – thanks to big data for blockchain.

The Close Ties Between Blockchain and Big Data

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Big data is comfortably dealing with huge sets of data, but some issues in its infrastructure have posed a problem in the widespread adoption of the technology. The big data infrastructure is centralized to a server location that offers complete unconditional control of data to the ones who have access to the server. This ‘ownership’ creates a problem when big data infrastructure is to be shared between different companies or even different regional offices of the same company. Besides, having multiple copies at different locations is not a solution because it puts a burden on resources and also creates confusion while determining the most updated data resource. Furthermore, now that big data resources are being traded among different entities, the legitimacy of a data resource poses a concern. With a blockchain for big data, we can create a decentralized data resource to which every one has full access. We can also track updates to the data resource on the blockchain, eliminating the need for and confusion due to multiple copies. Moreover, data transactions can be verified for legitimacy using blockchain concepts like proof-of-work or proof-of-stake and at the same time blockchain can provide a robust financial platform for data transactions between entities.

It is incredible how both of these technologies – big data and blockchain – can together significantly improve the usability of each other. The techniques can help create a hybrid infrastructure on pillars of big data and blockchain. The infrastructure will be flexible for different application types, like its parents – big data and blockchain.

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