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Data Ingestion

Each dataset is mapped into our Global Schema during ingestion, enabling users to directly compare different datasets.

InfoSum's Global Schema

We have defined a standard set of categories and keys, which can be used to compare datasets from diverse original sources, known as our Global Schema.

As part of the onboarding process, the data is converted to match the Global Schema. Because all datasets go through this process, they end up compatible with each other - even if their original schemas were different

Our data science team is constantly evolving our Global Schema to add new taxonomies based on demand or specific projects.

Flexible categories

InfoSum categories are a specific type of information contained in a dataset. Our Global Schema includes many possible categories, reflecting information commonly found in our customers' datasets.

Here are just a few examples of predefined categories:

Name
Age
Market Value Of Property
Date Of Vehicle Insurance Renewal

Custom categories for data which doesn't fit in any of the predefined categories can also be created by the user or ticketed for our data science team.

Data cleansing and transformations

Our ingestion process enables you to perform powerful data cleansing and transformations, 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, or to automate regular uploads.

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