As the team at Vision Insight AI continue to build in the intelligent way of doing Data Management. The world around us has one harder topic to consider i.e. Blockchain.
The current state of data is we are highly distributed by nature, for example banking, healthcare, transportation, energy, manufacturing, and other sectors, the trend is decentralized locations and teams managing local data. But it’s a trend that comes with the potential for chaos — especially for master data, where accuracy, security, and conformity are essential.
Most organization would have move on the idea of building Master Data Management capabilities as organic path of technology growth, they would write tons of ETL data pipelines on cloud of there choice OR on premise. ETL data pipelines or alternate technologies can be costly and after the multi man year project they still don’t seem to come to gospel truth of the “Single Source of Truth”.
A Quick catch up Blockchain
Blockchain is a distributed ledger that is encrypted and immutable. Each new block that is added to the chain needs to be verified by the previous block with a unique identifier. Blockchains are cloud-hosted (hence the term ‘distributed’).
So, while this is obviously useful for transactions and has traditional finance institutes scrambling because Blockchain can cut the middle man, Blockchain’s native safety features make it a great choice for what’s known as ‘the single source of truth’ as well.
How can Blockchain help in Master Data Management?
Master Data Management (MDM) depends on creating consensus truth for the enterprise which is e-commerce business. If Enterprise A merges with Enterprise B, their big stores of master data need to merge as well. It’s critical that the process reliably matches customer records when it should, while carefully avoiding false matches. Business can depend on the accuracy of the master data matching process.
Traditionally, matching has meant linking the records within the two different databases, based on identifiers like Customer Name, Address, date of birth, drivers’ license information, and so on. The MDM system could write the linkage information to a central database accessible from different locations. But having a single copy of the linkage data in a single location has meant that admins need to take special care to ensure that the data is highly available and secure. Private blockchain networks (also called ‘permissioned networks’) offer an intriguing alternative.
A better MDM solution with Blockchain
The Digital Ledger has much more to offer for example over time, large enterprises will adopt distributed ledger models to record and manage biographic and biometric data. For example, imagine hospitals, banks, and governments all wanting to maintain their master data on the blockchain. But those organizations will need ways to match and link that data across private networks.
The submission here is “One can build an MDM without necessarily having to go down the path of ETL, Data pipeline leveraging distributed ledger”
Consider Enterprise A and Enterprise B. If they each maintain their customer records, how will they combine those records in the event of a merger?
The enterprises could first create a business network using the blockchain technology. That offers an advantage because data sharing then happens on the blockchain network as opposed to being centralized. Once the teams create the network and begin sharing data on the network, sophisticated algorithms kick in to perform matching and linking — and the linking information is also stored natively on the blockchain.
Teams could also choose whether each node should maintain its own copy of the linkage information on the ledger. If not, the node can simply consume the linkage information that’s maintained elsewhere on the network. That option keeps transaction activity from swamping any nodes that might have less compute power or connectivity, while helping to ensure that the linkage data is stored redundantly across multiple nodes.
Hopefully, the e-commerce example puts a compelling argument on the potential advantages of MDM on the blockchain, but the gains don’t stop there. Consider…
ü Data reconciliation: When every participating business unit is part of the blockchain network, there’s no longer a need to move data between the business units. With traditional MDM, data movement can consume an enormous amount of time and energy.
ü Cost and Trust: Maintaining a central infrastructure is expensive and prone to security compromise. With the blockchain system, transactions aren’t committed without the consensus of the whole system.
ü Organizational efficiency: The blockchain eliminates the need for complex reconciliation between different nodes, whether the nodes are branch banks, health clinics, distribution centers, or other peers in the system.
ü Disintermediation: Eliminates central intermediaries and reduces the fear of arbitrage within the ecosystem.
ü Transparency: Enables audit trails to be established for assets and transactions, minimizing disputes.
Like all big data, master data offers important opportunities for machine learning analytics. Obviously, embedded analytics of anonymized master data can yield powerful insights, but machine learning can also play a role further upstream.
Morning Blaze find ways to apply machine learning to the matching process itself to ensure even higher confidence for the linkages between records.
Ultimately, the goal is to make Master Data Management as easy and intuitive as possible. New tools will give non-technical users across industries the ability to manage master data flexibly, efficiently, securely — and with perfect confidence.