Best Data Analysis Software for Amazon Web Services (AWS) - Page 2

Urban SDK is an urban data analytics platform that provides State and Local Governments with a transportation information system of record for traffic diagnostics, data management, and compliance tools to share information publicly. Our off-the-shelf traffic analytics software helps engineers, planners, and Public Works officials monitor and report traffic speeds on local roads. Users can quickly view roadway speeds, search for an address, and create traffic speed report. They can do this in 1-2 minutes without a hard count. Our mission is to allow customers to quickly identify issues serious enough to warrant spending time, money, and staff resources it takes to collect additional data. This enables cities to automate data collection, analysis, and estimate improvement costs on all local roads. Cities can save more than $200,000 annually by modernizing traffic data collection and reducing administrative burden with our smart traffic management software.

The Code Ocean Computational Workbench speeds usability, coding and data tool integration, and DevOps and lifecycle tasks by closing technology gaps with a highly intuitive, ready-to-use user experience. Ready-to-use RStudio, Jupyter, Shiny, Terminal, and Git. Choice of popular languages. Access to any size of data and storage type. Configure and generate Docker environments. One-click access to AWS compute resources. Using the Code Ocean Computational Workbench app panel researchers share results by generating and publishing easy-to-use, point-n-click, web analysis apps to teams of scientists without any IT, coding, or using the command line. Create and deploy interactive analysis. Used in standard web browsers. Easy to share and collaborate. Reuseable, easy to manage. Offering an easy-to-use application and repository researchers can quickly organize, publish, and secure project-based Compute Capsules, data assets, and research results.

ZinkML is a zero-code data science platform designed to address the challenges faced by organizations in leveraging data effectively. By providing a visual and intuitive interface, it eliminates the need for extensive coding expertise, making data science accessible to a broader range of users. ZinkML streamlines the entire data science lifecycle, from data ingestion and preparation to model building, deployment, and monitoring. Users can drag-and-drop components to create complex data pipelines, explore data visually, and build predictive models without writing a single line of code. The platform also offers automated feature engineering, model selection, and hyperparameter tuning, accelerating the model development process. Moreover, ZinkML provides robust collaboration features, enabling teams to work together seamlessly on data science projects. By democratizing data science, we empower companies to extract maximum value from their data and drive better decision-making.