4 MINUTE READ | April 4, 2018
The Promise of Blockchain and Standardized Data
If your role involves analyzing and utilizing data, you might have had one or two frustrating experiences with inconsistent data. Campaign names can be named differently across various channels and platforms — not to mention when there are typos in the campaign naming so they don’t fall under the same code logic – making manual data cleansing one of the biggest, most time-consuming, and least fun parts of the analytics process.
But luckily, we have an idea for how these problems can be fixed (or at least heavily improved) — blockchain. Originally created as a distributed digital ledger for the original cryptocurrency Bitcoin, Blockchain can be an answer to our prayers, solving data inconsistency problems across vendors, agencies, and client partners. Because it is an append-only, time-stamped ledger that is duplicated across all participants in the network, blockchain can prevent one party from tampering with or corrupting the data and make the whole process of data analysis and analytics more auditable. By looking at the core concepts of Blockchain, it’s easy to imagine how it can be used to solve data inconsistencies in marketing.
With Blockchain, all updates to the ledger are saved across every participant’s computer rather than saving in a centralized server. When a new block is added to the chain, each participant verifies the block and syncs across every ledger. This principle not only allows each participant to have the same set of data but also encourages the participants to standardize the data structure so it is understandable and accepted by every party in the chain. It will allow advertisers, publishers, and agencies in the digital marketing supply chain to have and operate off the same dataset — serving as a source of truth for everyone.
Each participant is given two identifiers when they join a Blockchain – a private key and a public key. Private key is a unique identifier of the participant, and public key is the derivative of the private key, and its hashed address is used for transactions to verify that the transaction is valid. This hash function prevents any data from being modified – as a completely different hash is generated every time someone tries to modify the data because it requires verification from every participant of the chain. This rigid process will prevent anyone in the marketing supply chain from tampering data without getting approval from everyone.
Once a block is generated, the transaction must go through a process called “mining” in blockchain – a set of calculations that is required in order to verify the transaction prior to adding it permanently to the chain. Even so, with a platform such as Ethereum, parties can implement smart contracts – enforcing pre-approved agreements with each transaction. So when a new marketing transaction is done, the industry can put an algorithm in place to verify if the transaction data is up to the standard that was agreed upon when the smart contract was created before adding it to the chain – ensuring the integrity of data prior to its generation.
In 2016, major insurance companies around the world such as Allianz and Zurich formed B3i, Blockchain Insurance Industry Initiative to research its usage in the industry. They launched a prototype of insurance industry blockchain in 2017 that allows the insurance companies to provide more streamlined and standardized contracts across the industry. With the implementation, insurance companies will be able to share data with each other and ensure that the data is the same all across the board.
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Blockchain is one of the most hopeful technology offerings since the dawn of e-commerce but before that hope turns into adoption, there needs to be defined use cases that can create credibility in the technology and investment against those use cases. Guess what, it’s happening. IDC is estimating $2.1B in spend against Blockchain solutions in 2018. Blockchain also requires a broader understanding to understand the proper usage of its capabilities or proper implementation of the platform. With the careful utilization of its core principles, we can move one step closer to the world all data analysts dream of – standardized data.
Posted by: Yun Lim
5 MINUTES READ | July 24, 2017