Build, deploy, and operate Enterprise AI applications.
Model Driven Architecture
Data Exploration
- Access up-to-date data from a unified data model across the organization. Loaded and virtualized data sources are available without writing complex joins, regardless of the persistence technology.
- Quickly access and explore raw data files uploaded to a Notebook or file system like Azure Blob storage, AWS S3, or on-premise SSD.
- Use pre-build no-code interfaces for viewing data, or code your own visualizations and data quality checks, productize your work as a reusable API that the whole team can access from Jupyter or any client.
Visualizations
- Identify patterns and trends by visualizing data in tables and charts.
- Generate insights by profiling data with histograms, identifying relationships with correlation matrices, and looking at scatter plots, line charts, bar charts, and area charts.
Jupyter
- Use Jupyter Notebook to view data stored in a unified data model.
- Easily fetch instances of a BHC3 Type, and view as tables in a notebook.
- Readily visualize and plot time series data.
- Use your favorite libraries to visualize and explore data.
Datasets
- Accelerate machine learning prototyping through high- performance, distributed, and in-memory exploration of large datasets from enterprise data sources.
- Auto-record selective data science experimentation steps and metadata for seamless AI application development and deployment.
- Enhance loading, organizing and profiling for unstructured and mixed data including images and text.
BHC3 Ex Machina
- Leverage BHC3 Ex Machina to load disparate data sources and join, filter, and wrangle data, all without having to write a single query. An easy-to-use, drag-and-drop interface gives users ready access to the power of data exploration.
- Quickly load data in a table and view dozens of prebuilt charts such as histograms, scatterplots, line charts, and correlation matrices. Start exploring data without writing a single line of code.