The emergence of cloud has successfully vanquished the challenges of data storage. With data proliferation being the norm in all domains, the focus of thought leaders is now on obtaining the right insights using big data analytics. Thanks to garbage-in-garbage-out, the results of analytics are only as accurate as the data that was analyzed. With multiple sources such as sensors and IoT systems feeding the data lakes and multiple stages of transformation associated with the analytics procedures, the scope for introducing errors into the data is high. Not surprisingly, no more than 30 percent of data scientists and analysts trust the results of their data analytics platforms, according to a survey by KPMG and Forrester.
Solutions to the data analytics problem have been found in the blockchain. The success and popularity of bitcoin has prompted industry experts to take cognizance of blockchain’s underlying technology and apply the same to other domains. Essentially, blockchain is a ledger with properties such as robust security, an immutable history of transactions within the blocks, time-stamping and consensus-driven mechanism for making changes to the ledger by means of proof of work and proof of stake. Blockchain emerges as the best solution in cases where private data is involved. The concept has been used to build tools such as BigChainDB on the MongoDB platform along with the ability to query the data and scale the system to perform other operations.
There are multiple use cases involving blockchain and big data. Among them is the electronic health records (EHRs) where interactions between doctors and patients generate huge amounts of data. Sharing the data with other physicians for better insights into the case, or even research purposes, is not easy as the records are known to contain errors which may percolate into the analytics process. Therefore, healthcare technology is being disrupted by blockchain. In a different instance, banks are leveraging blockchain to analyze their interbank transfers made by their customers, which not only keeps the data secure but also provides insights into the spending patterns.