Howso’s seamless integration with Databricks ecosystem empowers data teams with Understandable AI®, Causal AI, and Generative AI insights.
As organizations increasingly adopt cloud-native platforms to drive data insights and data-driven decision-making, seamless integration between tools becomes more crucial than ever. Howso—a cutting-edge platform offering out-of-the-box exploratory data analysis (EDA), Generative AI capabilities, and advanced validation—now fully integrates with Databricks, leveraging the power of Unity Catalog and MLflow to provide a holistic, end-to-end solution for AI/ML teams.
This integration allows Howso to enhance productivity across data teams, eliminating many time-consuming tasks traditionally associated with data science workflows. This also means that you can now find Howso on Databricks Partner Connect.
Let’s explore how Howso capitalizes on Databricks’ robust infrastructure and ecosystem, revolutionizing the way businesses handle their data with Causal AI and Generative AI.
1. Learn: Uncover Insights Effortlessly with Databricks
One of Howso’s key strengths lies in its ability to perform augmented exploratory data analysis (EDA). Traditionally, uncovering insights from vast datasets requires substantial manual effort and computational power. However, Howso’s integration with Databricks simplifies this process by performing fast, automated exploratory analysis across datasets, helping data scientists uncover AI insights with minimal effort.
Key learning capabilities of Howso include:
• Global, Conditional, and Local Analysis: By connecting directly to your data in Databricks, Howso can analyze features globally (across the entire dataset), conditionally (under different constraints such as dropped features or data points), and locally (at the individual prediction level), providing understandable AI that improves decision-making.
• Classification and Regression Stats: Howso automatically generates statistical outputs like accuracy, precision, recall, and more for classification tasks, along with mse, rmse, and r-squared for regression, offering a comprehensive snapshot of your dataset’s predictive capabilities.
• Null and Missing Value Analysis: Missing data is a common issue in data science workflows. Howso integrates with Unity Catalog to ensure comprehensive null and missing value insights, helping you address these problems early in your process.
Through this integration, Causal AI models can be better trained, allowing data scientists to assess the usability of their data quickly and avoid costly delays in the ML pipeline. Rather than investing time in model building only to discover issues later, Howso helps teams gain clarity upfront, making AI insights more accessible and actionable.
2. Generate: Empowering Generative AI without the Risk
The increasing demand for Generative AI opens up new avenues for innovation, but it also comes with challenges related to privacy, data drift, and model bias. Howso’s unique approach enables organizations to leverage Generative AI safely, ensuring that the data remains trustworthy and up-to-date without relying on traditional, retrained models.
Using Databricks’ powerful compute infrastructure, Howso can:
• Generate Private Synthetic Data: Howso creates synthetic data that maintains privacy through its anonymity preservation techniques, while ensuring that the synthetic data maintains the statistical integrity of the original dataset. This provides Causal AI insights into how data features are interconnected while safeguarding privacy.
• Eliminate Model Drift: With a live connection to Databricks, Howso remains in sync with your data, constantly adjusting as new data points come in. This approach eliminates model drift, opacity, and bias, common problems in traditional models that require frequent retraining.
• Synthesize Across Time-Series and Joined Tables: Howso can also generate time-series data and joined tables, ensuring you have the flexibility to create any dataset required for your specific use case, all while tracking the provenance and lineage of the generated data through Databricks’ Unity Catalog.
This integration ensures that data professionals can innovate with Generative AI tools while ensuring compliance and minimizing risks, thanks to the scalable, secure infrastructure provided by Databricks.
3. Validate: Detect and Address Data Drift Efficiently
A critical pain point for data science teams is monitoring model drift—when the data used to train models shifts over time, leading to performance degradation. Howso’s validation capabilities, enhanced by its integration with MLflow, ensure that models remain accurate, reliable, and explainable throughout their lifecycle.
Through its k-NN+ approach, Howso offers rapid and cost-effective drift detection that does not require extensive model retraining. It leverages the power of statistical measures for analyzing the surprisal of new data—identifying when data points deviate from expected patterns or distributions, which could indicate model drift, thus empowering Causal AI validation.
In addition to detecting drift, Howso also provides:
• Explanations for Model Predictions: By standing alongside your ML models, Howso can offer highly accurate feature importances, residuals, and counterfactual explanations for every prediction—ensuring data scientists fully understand their model’s behavior through understandable AI.
• Privacy and Utility Assessments for Synthetic Data: Howso’s validation framework evaluates synthetic data’s privacy and utility compared to the original data, ensuring that synthetic datasets are reliable enough for production use.
All validation results are automatically logged to MLflow and Unity Catalog, making it easy for teams to track performance metrics and model integrity over time, while also ensuring compliance with audit and privacy standards.
Conclusion
Howso’s integration with Databricks, Unity Catalog, and MLflow represents a significant leap forward for data teams seeking to streamline their workflows. By automating exploratory data analysis, enabling the safe use of Generative AI, and providing continuous validation through drift detection and Causal AI explainability, Howso empowers organizations to unlock the full potential of their data in ways that were previously unattainable.
This partnership ensures that teams can learn from their data, generate synthetic versions without compromising privacy, and validate models effortlessly—all within a secure, scalable ecosystem. With Howso and Databricks, your team is not only set to accelerate AI/ML development but also to innovate with confidence and agility.
To see how Howso could help your company unlock the full value of your ML/AI investments through data-centric explainability, you can request a demo here.