The Machine Learning Analytics Snap Pack provide Snaps for understanding and profiling your data before it enters machine learning models or analytics processes. Too often, data quality issues, unexpected formats, or statistical anomalies derail AI and analytics initiatives. Catching these problems early saves hours of troubleshooting. The Snap Pack gives you the diagnostic tools to examine your data structure, compute key statistical metrics, and validate data types across your datasets, all within your SnapLogic workflows.
Whether you’re preparing data for model training, validating data quality in production pipelines, or exploring new datasets to understand their characteristics, these Snaps provide the visibility and insights you need to work confidently with your data. Check your data health to ensure that what flows through your pipelines is clean, consistent, and ready for the sophisticated analytics and AI operations that follow.
This Snap Pack has the following Snaps:
- Profile: Enables you to compute statistics on the incoming data and analyze each field as either numerical or categorical.
- Type Inspector: Enables you to inspect and analyze the data types present in the data set for information about the structure and format of the data.
To learn more, please check out the documentation page.
