Data Science Collaboration

Data scientists and analysts struggle with how to collaborate in the most efficient way. Data science collaboration tools can reduce this friction and enable teams to solve their most critical business-analytics problems.

These are just a few examples of data science collaboration solutions. Scroll down or use the drop-down menu to learn more about each solution.

Choose a solution
  • Choose a solution
  • Saturn Cloud
  • Machine Metrics

Saturn Cloud

Saturn Cloud is a data science and machine learning platform designed to accelerate runtime performance using multi-node multi-GPU computing in Python. It enables you to provision scalable cloud resources on demand to execute workloads across the ML pipeline, from data ingestion, exploratory data analysis, feature engineering, training, and deployment. Saturn supports the full Python ecosystem as an enterprise-ready, secure, and collaborative high-performance computing platform.

Saturn Cloud features include:

  • Customizable HPC Environments
  • Multi-node, multi-GPU computing
  • Instant elasticity
  • Managed deployments
  • Team collaboration and centralized version control
  • Per-second billing with no commitments

How it works

Additional resources provided by Saturn Cloud

AdventHealth

AdventHealth needed a historical review of its investment strategy to determine how a portfolio performed over time. Since the algorithm used to derive this information was computationally intensive, AdventHealth turned to Saturn Cloud’s parallel computing capabilities to help streamline this process. By adopting Saturn Cloud, AdventHealth reduced the runtime to just seconds and boosted its ability to perform more portfolio backtests quicker and at scale.

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We had a portfolio backtest taking nearly 20 minutes to run before the team at Saturn Cloud took a look at it. Between advising us on our code and dispersing the work across parallel processing via Dask, this backtest was completed at a rate several hundred times faster, taking only a few seconds to execute.

Greg Ringering, Quantitative Investment Researcher, AdventHealth

MachineMetrics

MachineMetrics is an IIoT analytics platform that increases productivity through real-time visibility, deep analytics, and AI-driven predictive notification. Businesses using MachineMetrics gain real-time visibility of their production assets, identify inefficiencies, and receive automatic recommendations for asset performance improvement resulting in increased profitability.

MachineMetrics features include:

  • Universal machine connectivity
  • Configurable AI-driven preventive and predictive analytics
  • IoT cloud data infrastructure
  • Real-time dashboards, historical analysis, and integrations with other systems

How it works

Additional resources provided by MachineMetrics

Wiscon Products

Wiscon Products wanted to improve the efficiency of their assets and overall equipment effectiveness. The company turned to MachineMetrics for its AI-driven, real-time, predictive and preventive data analysis. Using MachineMetrics, the company increased operator productivity by 250%, overall capacity by 30%, and equipment utilization by 30%.

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MachineMetrics was pivotal in our efforts to integrate with our JobBOSS ERP system. Now our operators can focus on quality, not administration or data entry. This has become a huge advantage in getting good, real-time information, as well as greatly improving operator efficiency.

Torben Christensen, President/CEO, Wiscon Products
AWS Marketplace

AWS Marketplace is a digital catalog with thousands of software listings from independent software vendors that make it easy to find, test, buy, and deploy software that runs on AWS.

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We're here to help you get started with AWS Marketplace. Ask for or give advice on the AWS Marketplace discussion forum.

Have questions? Have tips?

We're here to help you get started with AWS Marketplace. Ask for or give advice on the AWS Marketplace discussion forum.