SPARK Integrations

The Domino Enterprise MLOps Platform helps data science teams improve the speed, quality, and impact of data science at scale. Domino is open and flexible, empowering professional data scientists to use their preferred tools and infrastructure. Data science models get into production fast and are kept operating at peak performance with integrated workflows. Domino also delivers the security, governance and compliance that enterprises expect. The Self-Service Infrastructure Portal makes data science teams become more productive with easy access to their preferred tools, scalable compute, and diverse data sets. By automating time-consuming and tedious DevOps tasks, data scientists can focus on the tasks at hand. The Integrated Model Factory includes a workbench, model and app deployment, and integrated monitoring to rapidly experiment, deploy the best models in production, ensure optimal performance, and collaborate across the end-to-end data science lifecycle. The System of Record has a powerful reproducibility engine, search and knowledge management, and integrated project management. Teams can easily find, reuse, reproduce, and build on any data science work to amplify innovation.

Wherobots allows users to develop, test and deploy AI and geospatial data pipelines within their existing data stack. This can be deployed on the cloud. Users do not have to worry about the hassle of resource administration, workload scalability, and geospatial processing support/optimization. Our SaaS interface allows you to connect your Wherobots Account to the cloud database that stores the data. Sedona Developer tool allows you to develop your geospatial data analytics, machine learning or analytics applications. Schedule automatic deployment of the geospatial data pipeline to the cloud platform and monitor performance in Wherobots. Consume the results of your geospatial analysis task. The consumption model is a single geospatial mapping visualization or through API calls.

No more data catalog ghost cities. Acryl Cloud accelerates time-to-value for data producers through Shift Left practices and an intuitive user interface for data consumers. Continuously detect data-quality incidents in real time, automate anomaly detecting to prevent breakdowns, and drive quick resolution when they occur. Acryl Cloud supports both pull-based and push-based metadata ingestion to ensure information is reliable, current, and definitive. Data should be operational. Automated Metadata Tests can be used to uncover new insights and areas for improvement. They go beyond simple visibility. Reduce confusion and speed up resolution with clear asset ownership and automatic detection. Streamlined alerts and time-based traceability are also available.

Built and maintained by a group of differential privacy experts and used in production at institutions such as the U.S. Census Bureau. Spark-based and supports input tables with billions of rows. Supports an ever-growing number of aggregation operators, data transformation operators and privacy definitions. Perform public and privacy joins, filters or user-defined function on your data. Calculate counts, sums and quantiles under multiple privacy models. Our simple tutorials and extensive documentation make it easy to differentiate privacy. Tumult Analytics was built on Tumult Core - our sophisticated privacy foundation. Tumult Core mediates access to sensitive information and means that each program and application has an embedded proof of security. Composed of small, easily-reviewable components. Stability tracking and floating point primitives that are proven to be safe. Generic framework based on peer reviewed research.