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Our automated normalisation and mapping process ensures no changes are required to the original data to make it compatible across multiple data sources.
With so many different data formats and taxonomies in the data economy, analysis across multiple datasets has required costly and time-consuming ETL exercises.
Our identity infrastructure includes an AI-powered standardisation process that takes the various attribute data in first-party data sources and automatically map them to our extensive global schema. For example, the various representations of age are mapped to several commonly used age brackets.
This process ensures analysis can be seamlessly conducted across multiple data sources, without expensive and complex ETL processes.
This standardisation process enables you to perform powerful data cleansing and transformations, so you can shape your data after import. This removes the need to make any changes to the original data.
Our Global Schema contains over two hundred predefined categories and keys, which can be used to compare datasets from diverse sources. Because all datasets go through this process, they all speak the same language, irrelevant of their original taxonomies.
Custom categories can be created on the fly for any attributes that are currently not represented in our Global Schema. Additionally, new categories can be added to our Global Schema where required.
We don’t hold any data. We provide the identity infrastructure to power a decentralised ecosystem.
Federated technology keeps your data in its own unique Bunker, that only you can access.
You remain in control of who can analyse your data. This never grants access to the raw data.
First-party data sets are matched using existing identifiers, removing the need to share data.
Our proprietary Insight Engine generates a virtual database that enables multiple data sources to be analysed without moving, centralising or sharing data.
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We utilise differential privacy concepts during both analysis and activation to safeguard personal data and ensure no individual can ever be identified within our UDP.
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Our technology doesn’t rely on a single ID or identity graph. Instead it automatically determines the identifier, or combination of identifiers, within the dataset to create the optimal match.
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Our rich permissions management ensures data owners remain in control of who can use their data in their analysis, and to what extent it can be analysed.
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Our automated normalisation and mapping process ensures no changes are required to the original data to make it compatible across multiple data sources.
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Our identity infrastructure is built on a federated architecture that ensures all datasets remain decentralised in their own isolated Bunker, but can be analysed ‘as one’.
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InfoSum’s identity infrastructure has been built on six core technologies that empower trust by allowing data to remain decentralised, while enabling multiple first and second-party data sources to be connected for analysis and activation.
