Data Tokenization Explained: What Is It And How Does It Work?

    Data breaches have been an increasing trend causing major losses, especially for big companies. This security violation also affects individuals on a smaller scale. Hence why new solutions are continuously suggested to protect one’s data and privacy. Data tokenization is the process of turning data into a token. But, how does this work and protect your sensitive information?

    What Is Data Tokenization?

    Data tokenization is the process of turning sensitive data into a non-sensitive element known as a token. A token is simply the representation of the asset, or data, whether it’s physical or digital. 

    It enables you to use the “representation” of your data without having to disclose the sensitive data itself. The idea is that you’d use the token freely without having to worry about continuously sharing your private information with everyone. 

    Is It The Same As Encryption?

    You might be thinking that this seems similar to encryption. However, encryption and tokenization are two different processes.

    Encryption is the process of turning plain text of data into a cipher text. The latter is unreadable without a secret key. However, tokenization completely replaces the data with a token. And you can access the original data by using the token itself without needing a secret key.

    Encryption vs Data Tokenization

    How Does Data Tokenization Work?

    Let’s say you want to tokenize your credit card information. How would you do this? There are different ways to tokenize data some depending on the existence of a vault, while others operate without one. And, there’s also tokenization on the blockchain. 

    Vault Data Tokenization

    Vault data tokenization involves storing sensitive data, as well as the token, in a secure database. A great example of this is on-demand data random assignment-based tokenization (ODRA).

    On-Demand Random Assignment-Based Tokenization (ODRA)

    On-Demand Random Assignment-Based Tokenization (ODRA) was one of the initial techniques used to tokenize data. This process relies on the existence of a “vault” or database. For every new element, a new mapping is created in a database. However, the mapping is random.

    ODRA Tokenization

    Following the example above, for the value “x”, the system randomly creates a token that can be anything from “a” to “f”. 

    If the users wanted the original data, the tokenized system detokenizes the data in respect of the mapping. So it conducts the reverse of the random function that generated the token.  If the mapping is found, clear text is provided.

    However, given that for every item there has to be a mapping, the database is constantly growing making it hard to maintain. Given the size of the database, detokenization can take a long time. In order to deal with these limitations, vaultless tokenization systems were introduced. 

    Vaultless Data Tokenization

    Vaultless data tokenization is an alternative to vault tokenization. As the name suggests, this type of tokenization doesn’t include a database but can either rely on static tables or cryptography. 

    Static Table Based

    Static table-based data tokenization uses an algorithm that generates tokens based on a static pre-generated table. There isn’t any token mapping in this technique. Rather, each value will have its own unique token.

    Static Table

    Following the example above, the value “x” will have a token a or b. The tables are typically small enough, and given that there is no mapping, they’re easier to manage. Moreover, detokenization is easier in this context because the tables are pre-determined. 

    Encryption Based or Format Preserving Encryption (FPE)

    Encryption-based tokenization follows the advanced encryption standard (AES) algorithm to generate a token. In order to access the original data, you would need the “secret key”. The same key is used to encrypt and decrypt the data. 


    Blockchain Tokenization

    Blockchain tokenization divides asset ownership into multiple tokens. This opens up a large window of opportunities for dApp development and rising projects. There are three distinctive tokenization on the blockchain that we’ll tackle below. 

    NFT Tokenization

    NFTs, or non-fungible tokens, are one of the most popular tokenization on the blockchain. They are digital data representing unique assets. These assets don’t have a pre-determined value, hence the “non-fungible” terminology. Each holds its own unique value. 

    NFTs are used as proof of ownership allowing users to trade and own items on the blockchain. There is an influx of NFT projects from digital art to games to real estate. 

    Governance Tokenization

    Governance tokens are directly linked to voting systems on the blockchain. They’re used to make better decisions while maintaining decentralization. 

    Utility Tokenization

    Utility tokens are created using a protocol that allows access to multiple services within that protocol. Their value is centered around the utility that they provide. 

    Should You Tokenize Your Data?

    Data tokenization enhances security and is a step in the right direction toward protecting yourself. But, it also has its own limitations. 


    • Increases data security. By replacing sensitive data with a non-sensitive token, it reduces the exposure of the information which, in turn, reduces the risks of data breaches. 
    • Enables secure data sharing. By sharing a representation of your data, you’re keeping it secure. The original data remains protected.
    • Lessens the need for data control. Given that the tokens aren’t sensitive, there is no need for extensive data control.  
    • Enhances dApp development. Tokenization on the blockchain improves the capabilities of dApps, as well as multiple projects. 
    • Creates a segway for web2 brands into web3. Big web2 brands can implement data tokenization to solidify their presence on the blockchain. Thus widening their target market. 


    • Affects data quality. During data tokenization, some information might be lost or distorted. 
    • Causes interoperability of data. Data tokenization can make it difficult for users to use their data across multiple platforms. 
    • Raises legal questions. There aren’t clear legal regulations over tokens so it might cause legal issues over who owns and control the data. 
    • Complicates data recovery. Detokenization isn’t a smooth process especially if using systems based on mapping algorithms. 

    Whether you should tokenize your data or not is a personal decision. However, it’s important to consider both viewpoints before taking any step. And it has to be useful to do so. Otherwise, you’d have overcomplicated you accessing your data for no reason. Nevertheless, data tokenization holds big opportunities for successful projects if implemented correctly. 


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