While it is a newer technology, blockchain is already disrupting financial services, insurance, healthcare and supply chain solutions. Two main causes of this disruption are blockchain’s ability to enable disintermediation, and how it provides an immutable historical record of data. Blockchain technology itself solves many of the problems that data governance professionals, and data management technology vendors have been trying to solve for years: group consensus on the most recent version of the truth for a given entity, and full instance lineage (provenance) of the data.
While blockchain has been able to transform these solutions, forward-thinkers are asking: will blockchain have the same disruptive effect on data management? There are two main factors to consider when assessing blockchain’s potential to disrupt data integration, storage, and data integrity:
Factor 1: Multiple Data Schema Affects Blockchain’s Efficiency
Blockchain technology at its core is a data store — a data store that represents a digital ledger of records (blocks) that are cryptographically linked (chained) to each other in historical sequence and distributed in a network. Data in the blockchain itself is a combination of reference and transactional data. New blocks are added to the chain only if network participants are able to come to a consensus that proposed changes to the data are valid. Once consensus is reached, every network participant gets the most recent version of the data; the elusive “golden record.”
Before getting too excited about blockchain disrupting master data management software and solutions, it’s important to understand that each blockchain could be for a different entity, and will likely have a different data schema, and may have a different version of the truth. Master data management rules, processes and technology may be needed to consolidate reference data across multiple chains.
Factor 2: Few Actual Implementations Hinders Disruption
Another key consideration of whether or not blockchain will disrupt data integration, is that there are very few if any, greenfield implementations in the enterprise. While the functions of the blockchain may be able to act independently of legacy systems, at some point blockchains will need to be integrated with systems of record. Data integration functionality inclusive of transformation, normalization and quality management may also have a place in smart contracts which are executable code distributed inside blockchains.
While there will be opportunities for data integration technologies and applications in blockchain implementations; data compliance, governance, and integrity is where blockchain will cause the most disruption. If everyone is responsible for the data, nobody is responsible – the reason for existing data governance organizations, processes, and supporting technology.
Yet blockchain disintermediates control through the use of consensus and everyone is responsible for the data. Who is responsible and how is dependent on the implementation being on a public permissionless, or private permissioned network. Bitcoin and Ethereum are examples of public permissionless blockchains. Hyperledger and Ripple are examples of private permissioned blockchains. Private permissioned blockchains are increasingly using the term Distributed Ledger Technology (DLT) to help distance it from Bitcoin and Ethereum, partly due to the recent issues and controversies of cryptocurrencies.
Efficiency in Blockchain
There continues to be a concern about transaction performance in blockchain, and whether or not it is truly efficient. Efficiency is something that needs to be understood in context. Today it takes days to settle a financial trade because financial institutions need to mediate the transfer of funds. In a distributed ledger or blockchain version of a trade, settlement happens once consensus is gained. In a public permissionless network such as Bitcoin, this can take up to 10 minutes, but 10 minutes is much more efficient than days. Transactions in private permissioned blockchains are typically better performing because all parties are trusted and consensus mechanisms aren’t as elaborate. High volume, low latency transaction processing applications may not be appropriate for blockchain technology yet, but in applications where data integrity is paramount, a little extra time to achieve immutable data provenance maybe acceptable.
Standards, cooperation, and competition will be critical to blockchain technology success. IDC has identified the four forces driving blockchain and DLT development, inclusive of industry vertical institutions, technology vendors, regulators, and consortiums. It is only fitting that blockchain innovation comes from a network of participants, given the technology itself is meant to be used by a network of participants, and not controlled by any one party.
Want to learn more about blockchain’s potential for data management disruption? Check out IDC’s report, “Blockchain — A Data Management, Integration, and Integrity Disruptor?” for more detail on how blockchain works at the data level.