C3 AI Platform

Preparation

Explore, wrangle, and standardize your data

Deep-Code Exploration​

Rich data exploration and visualization tools allow users to interactively explore raw data sources while working with preferred execution engines. Data scientists, engineers, and developers can leverage JupyterLab and Visual Studio Code available with C3 AI Studio, or work in C3 AI’s enterprise-grade Pandas interface.​

No-Code Exploration​

Interactive drag-and-drop canvas interface offers users no-code data exploration and visualization. Citizen data scientists and business analysts can easily explore, visualize, analyze, and share enterprise-scale data and insights through an integrated experience with C3 AI Ex Machina.

Profiling and Quality​

A powerful profiling and quality framework enables users to assess the data quality for datasets of any size. Teams can use out-of-the-box data quality checks or author their own via a rich library of expression functions to automatically detect data merge, deduplication, anomaly, outlier, sparsity, and connectivity issues.​

Unified Data Image​

A unique abstraction layer across the whole data infrastructure allows for universal APIs, connecting the user to data wherever it resides. With this architecture, data engineers can build a common data image, explore and visualize data on a development canvas, and prepare data for downstream analytics.​

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Timeseries Engine​

Automatically integrate, clean, normalize, and persist timeseries data. The timeseries engine on the C3 AI Platform was built to complete complex tasks quickly: define and set deduplication and overlap-handling​; leverage native normalization or calendarization to align time zones, units and intervals; and seamlessly configure and manage timeseries data across hot and cold storage to reduce costs.​​

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