What types of data can Kumo ingest?

Kumo supports the ingestion of various data source types by allowing you to configure connectors for the following:

• AWS S3 (CSV or Parquet files)
• Snowflake - Tables and Views
• Databricks - Tables and Views
• Google Cloud BigQuery - Tables

You also have the option of uploading a local file (CSV or Parquet files less than 1 GB) for ingestion into Kumo. In this case, you can skip connector creation and create a Kumo table directly by selecting Local File Upload.

In terms of data preprocessing, Kumo automatically preprocesses several data types when creating your Kumo table columns, including:

• Numerical: Integers, floats
• Categorical: Boolean or string values typically a single token in length
• Text: String values typically multiple tokens in length, where the actual language content of the value has semantic meaning
• Multi-categorical: Concatenation of multiple categories under a single string representation
• ID: Numerical values used to uniquely identify different entities
• Timestamp: Time/date information (for extracting year/month/date/hour/minute when applicable)
• Embeddings: Consist of lists of floats, all of equal length, and are typically the output of another AI model.
• Column types are automatically detected using heuristics on the distribution of values in each column’s data, and can also be manually configured.

Learn More:

• Data Connectors
• Create Table
• Column Selection
• Column Preprocessing