Best Data Science Software for Databricks Data Intelligence Platform

Find and compare the best Data Science software for Databricks Data Intelligence Platform in 2024

Use the comparison tool below to compare the top Data Science software for Databricks Data Intelligence Platform on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Zing Data Reviews
    You can quickly find answers with the flexible visual query builder. You can access data via your browser or phone and analyze it anywhere you are. No SQL, data scientist, or desktop required. You can learn from your team mates and search for any questions within your organization with shared questions. @mentions, push notifications and shared chat allow you to bring the right people in the conversation and make data actionable. You can easily copy and modify shared questions, export data and change the way charts are displayed so you don't just see someone else's analysis but make it yours. External sharing can be turned on to allow access to data tables and partners outside your domain. In just two clicks, you can access the underlying data tables. Smart typeaheads make it easy to run custom SQL.
  • 2
    Taipy Reviews

    Taipy

    Taipy

    $360 per month
    In no time, you can go from simple web applications to production-ready ones. No compromises on performance, customization and scalability. Taipy optimizes rendering by caching graphical events and enhancing performance. Taipy's decimator for charts intelligently reduces the number of datapoints to save memory and time without losing the essence. Every data point requires processing, resulting in slow performance and excessive memory usage. Large datasets can be cumbersome and complicate data analysis. Taipy Studio makes it easy to create scenarios. A powerful VS Code Extension that unlocks a convenient graphical Editor. You can schedule your methods to be invoked at certain times or intervals. You can choose from a wide range of predefined themes, or create your own.
  • 3
    Mode Reviews

    Mode

    Mode Analytics

    Learn how users interact with your product and identify opportunities to help you make product decisions. Mode allows one Stitch analyst to perform the work of a full-time data team with speed, flexibility, collaboration. Create dashboards for annual revenue and then use chart visualizations quickly to identify anomalies. Share analysis with teams to create polished reports that are investor-ready. Connect your entire tech stack with Mode to identify upstream issues and improve performance. With webhooks and APIs, you can speed up team workflows. Learn how users interact with your product and identify areas for improvement. Use marketing and product data to identify weak points in your funnel, improve landing page performance, and prevent churn from happening.
  • 4
    Alteryx Reviews
    Alteryx AI Platform will help you enter a new age of analytics. Empower your organization through automated data preparation, AI powered analytics, and accessible machine learning - all with embedded governance. Welcome to a future of data-driven decision making for every user, team and step. Empower your team with an intuitive, easy-to-use user experience that allows everyone to create analytical solutions that improve productivity and efficiency. Create an analytics culture using an end-toend cloud analytics platform. Data can be transformed into insights through self-service data preparation, machine learning and AI generated insights. Security standards and certifications are the best way to reduce risk and ensure that your data is protected. Open API standards allow you to connect with your data and applications.
  • 5
    Hex Reviews

    Hex

    Hex

    $24 per user per month
    Hex combines the best of notebooks and BI into a seamless, collaborative interface. Hex is a modern Data Workspace. It makes it easy for you to connect to data and analyze it in collaborative SQL or Python-powered notebooks. You can also share work as interactive data apps or stories. The Projects page is your default landing page in Hex. You can quickly find the projects you have created and those you share with others. The outline gives you an easy-to-read overview of all cells in a project's Logic View. Each cell in the outline lists all variables it defines and any cells that return an output (chart cells or Input Parameters cells, etc.). Display a preview of the output. To jump to a specific position in the logic, you can click on any cell in the outline.
  • 6
    Alteryx Designer Reviews
    Drag-and-drop and generative AI tools enable analysts to prepare and blend data up 100 times faster than traditional solutions. Self-service analytics platform gives analysts the power to remove costly bottlenecks and empowers them. Alteryx Designer, a self-service analytics platform, empowers analysts by allowing them to prepare data, blend it, and analyze it using intuitive drag-and-drop tools. The platform integrates with over 80 data sources and supports 300 automation tools. Alteryx Designer, with its focus on low-code/no-code capabilities, allows users to create analytic workflows easily, accelerate analytics processes using generative AI and generate insights, without needing to have advanced programming skills. It is also highly versatile, allowing the output of results into over 70 different tools. It is designed to be efficient, allowing businesses to speed up the preparation and analysis of data.
  • 7
    Knoldus Reviews
    The largest global team of Fast Data and Functional Programming engineers focused on developing high-performance, customized solutions. Through rapid prototyping and proof-of-concept, we move from "thought to thing". CI/CD can help you create an ecosystem that will deliver at scale. To develop a shared vision, it is important to understand the stakeholder needs and the strategic intent. MVP should be deployed to launch the product in a most efficient and expedient manner. Continuous improvements and enhancements are made to meet new requirements. Without the ability to use the most recent tools and technology, it would be impossible to build great products or provide unmatched engineering services. We help you capitalize on opportunities, respond effectively to competitive threats, scale successful investments, and reduce organizational friction in your company's processes, structures, and culture. Knoldus assists clients in identifying and capturing the highest value and meaningful insights from their data.
  • 8
    NVIDIA RAPIDS Reviews
    The RAPIDS software library, which is built on CUDAX AI, allows you to run end-to-end data science pipelines and analytics entirely on GPUs. It uses NVIDIA®, CUDA®, primitives for low level compute optimization. However, it exposes GPU parallelism through Python interfaces and high-bandwidth memories speed through user-friendly Python interfaces. RAPIDS also focuses its attention on data preparation tasks that are common for data science and analytics. This includes a familiar DataFrame API, which integrates with a variety machine learning algorithms for pipeline accelerations without having to pay serialization fees. RAPIDS supports multi-node, multiple-GPU deployments. This allows for greatly accelerated processing and training with larger datasets. You can accelerate your Python data science toolchain by making minimal code changes and learning no new tools. Machine learning models can be improved by being more accurate and deploying them faster.
  • 9
    Daft Reviews
    Daft is an ETL, analytics, and ML/AI framework that can be used at scale. Its familiar Python Dataframe API is designed to outperform Spark both in terms of performance and ease-of-use. Daft integrates directly with your ML/AI platform through zero-copy integrations of essential Python libraries, such as Pytorch or Ray. It also allows GPUs to be requested as a resource when running models. Daft is a lightweight, multithreaded local backend. When your local machine becomes insufficient, it can scale seamlessly to run on a distributed cluster. Daft supports User-Defined Functions in columns. This allows you to apply complex operations and expressions to Python objects, with the flexibility required for ML/AI. Daft is a lightweight, multithreaded local backend that runs locally. When your local machine becomes insufficient, it can be scaled to run on a distributed cluster.
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