A representation of the data is held in a secure decentralized network of cloud containers, known as Bunkers. Each Bunker is private to the specific dataset, maintaining data isolation and storage limitation to help clients comply with GDPR.
Bunkers are held on their own isolated subnets within a private Virtual Private Cloud, and all communications with the Bunker are protected by TLS 1.2 (HTTPS). Rigorous firewalling further restricts the network traffic entering or leaving a Bunker.
Once an Insight dataset is mapped through the InfoSum Platform, the raw data - including all personally identifiable data - is permanently deleted from the Bunker.
Insight Bunker datasets contain the representation of the keys and category information uploaded and mapped into them.
Containing no Personally Identifiable Information, Insight bunkers ensure safety and security for your data and consumers.
Our permission system ensures that only users you authorize will have permission to access insight from your bunker.
Identity Bunkers contain only a list of identity keys. Identity Bunkers are only available for accounts that have opted for Identity access, and can only be used with Insight Bunkers where permission has been given access.
Identity queries allow the exporting of the keys that match the set criteria. These can then be used for activation within campaigns.
Our technology automatically determines the identifier, or a combination of identifiers, to use to create the best connection between datasets.
Additionally, we are able to combine both unique and non-unique identifiers to generate the best identity match. We have a range of solutions for matching ‘fuzzy’ identity data, such as name and surname.
Our identity resolution approach puts privacy at the forefront. When matching identities across datasets, the unique identifiers are never transmitted, the match is completed through a series of secure bloom filters.
Additionally, we apply a range of differential privacy concepts, that allow insights to be gained from datasets while making it impossible to extract information about a single individual.
Obscures the source data by rounding the result up or down.
Adds a small amount of deterministic fuzziness to protect individual privacy.
Data owner defines the minimum bucket size returned in the query.
Prevents over collection of data and over use of the platform.
Our resolution does not require a single unique identifier across all datasets to create a match.
Different sets of identifiers can be used across different datasets for analysis, depending on the quality of the connection. For example, where Dataset A is being matched to Dataset B on email, it can be matched to Dataset C on mobile ID.
Third-party identity graphs can then be used to allow datasets that don’t share any common identity data.
The technology automates data transformations by mapping each dataset into a global schema. This enables users to normalize and anonymize multiple datasets, without adapting the source data.
Our Global Schema currently has over 150 different taxonomies that can be mapped to.
Additionally, our Global Schema has been built to be incredibly flexible, allowing us to add new taxonomies based on demand or specific projects.
Our powerful Global Schema enriches your data with additional information and useful additions such as binning and groups.
For example, when mapping address data the platform will automatically append the properties UDPRN - a unique universal reference for every postal address. UDPRN then becomes the key for address - allowing the platform to link data regardless of how the address has been entered.
Extra spaces and variations in address format are no longer an issue with InfoSum.
Our ingestion process allows you to perform robust data cleansing and transformation, so you can shape your data after import.
Our flexible Data Transformation Language (DTL) enables you to perform any transformations your data requires. Your configurations can be saved and reused by you for any datasets that share the same attributes.
InfoSum’s Query Engine allows you to delve into the insights contained within the combined data using our proprietary InfoSum Query Language. IQL is an intuitive querying language designed to let you ask the question you’d like about your data.
Our query engine can be accessed through our web interface, our REST API, or through connectors into common Business Intelligence tools such as Tableau, Google Data Studio or PowerBI. This flexibility allows you to integrate Infosum into your existing reporting processes with ease.
Infosum’s REST API gives you a powerful interface directly into our platform. Our REST API is perfect for when you want to query your datasets straight from your preferred visualization tool or even if you want to integrate Infosum’s unique capabilities into your own product.
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