The clean room data collaboration platform to accurately match name and address data

Data Clean Rooms describe the ability for two or more organisations to analyse their data in a shared environment, without exposing the original unencrypted data with each other, thereby completely removing the risk of personal and other sensitive data from being exposed or lost. 

95% of all organisations utilise cloud platforms to host their customer data.  Data Clean Rooms provide added security and also remove the requirement to go through lengthy processes to obtain permission from Infosec and legal teams to allow customer data to be released.

Application Programming Interfaces (APIs) are a core component of web-based applications which are accessible from any device with an internet connection. For example, an API would allow an app in your web browser to communicate with a server-side application or, alternatively, enable a web-based application to retrieve data from a database.  As such, data has to be passed from one computer to another via the internet, increasing the risk that a hacker may be able to intercept any data be transmitted.

Data Clean Rooms never expose the original unencrypted data, making them inherently more secure than an API.

Our LinkedIn article explains the benefits of a Data Clean Room over an API – https://www.linkedin.com/pulse/secure-data-management-clean-rooms-modern-alternative-nohfe/?trackingId=N1ABKyD%2FQjlA7pPp%2B7QJbw%3D%3D

JetStream offers enhanced secondary data security in a number of ways:

• Personally Identifiable Information (PII) is anonymised by converting customer data into pseudonymous irreversible match-keys, which are then used for all matching going forward
• All data matching takes place within the client’s own cloud-based account, meaning no data is shared outside of the organisation, eliminating any risk of a data breach when data is transferred

The transfer of sensitive PII data into pseudonymous keys that can be used in place of PII throughout the organisation helps infosec teams meet their objectives in reducing data loss risks and meeting GDPR data minimisation rules

As a human, recognising two addresses to be the same is intuitive and subtle differences don’t really matter, but the slightest difference to a computer, even the inclusion of a comma or a space, results in it failing to recognise them as the same. 

As humans we look at addresses and understand key words identifying which parts of an address indicate building names and street names for instance.  Whilst there are files of addresses to “look-up” against, even matching to these requires intelligence.  The same applies to nick names and common data capture errors.  A human recognises that Andy MacDonald and Andrew McDonnald are the same person, again something impossible for a standard computer comparison.

To overcome the intricacies of name and address matching it is necessary to use a solution which can recognise names and addresses to be the same, even when there are subtle or slight differences between them.  JetStream uses AI to recognise and understand keywords and patterns in names and addresses and cleans and standardises simpler data sources such as mobile numbers (dealing with country codes), email addresses and account numbers, converting them into irreversible pseudonymous match keys that can be used instead, making matching by computers extremely easy and meaning that the identification of customers who appear within or across disparate data sources is quick and efficient.  The irreversible pseudonymous keys produced by JetStream are ideal for use in Data Clean Rooms for customer data matching.  

Most data clean rooms offer a very basic data match between data sources.  Typically, matching is performed using email address, mobile number or IP address, often ignoring completely the name and address of the customer.

Unlike other data clean room solutions, JetStream provides highly accurate, multi-level matching using name, address, e-mail, mobile and other customer identifiers (such as IP addresses / customer IDs).   This provides a more advanced matching capability, ideal for use in creating single customer views (SCVs) for example.

Additionally, JetStream means the organisation keeps full control of their data as it never needs to leave their own cloud account, reducing the risk of data breaches and reducing the time and resource required to implement the data clean room solution.

JetStream also provides proactive updates to third-party datasets, meaning that when a dataset is updated, the changes occur in real-time in the customer table.

Currently JetStream works on the Snowflake platform hosted on either AWS, GCP or Azure. 

We are expanding JetStream to work on all major cloud platforms in the coming months.

JetStream comes with an in-built solution to graphically show how a group of records has matched, showing which elements of the name, address, email etc have matched.  This is particularly useful for DSAR look-ups.

No, JetStream does not alter the underlying PII.

The speed of processing is determined by the size of the Snowflake Warehouse.  Using an XS warehouse JetStream will easily process 1 million customer records in under 30 seconds.

Built in regression tests ensure consistency in logic even across application updates.