Best Data Management Software for R

JMP, data analysis software Mac and Windows, combines powerful statistics with interactive visualization. It is simple to import and process data. Drag-and-drop interface, dynamically linked graphics, libraries of advanced analytics functionality, scripting language, and ways to share findings with others allow users to dig deeper into their data with greater ease. JMP was originally developed in 1980 to capture the new value of GUI for personal computers. JMP continues to add cutting-edge statistical methods to the software's functionality with every release. John Sall, the organization's founder, is still Chief Architect.

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.

One source of truth for R packages and Python packages RStudio is the preferred professional data science solution for every group. A Python and R integrated development environment with syntax-highlighting editor, console, and code execution. It also includes tools for workspace management, history, plotting, and plotting. You can publish and distribute data products throughout your organization. One-button deployment of Shiny applications and R Markdown reports, Jupyter Notebooks, etc. To increase reproducibility and reduce the time spent installing and troubleshooting R packages, you can control, organize, and manage your use of them. RStudio is committed to sustainable investment in open-source and free software for data science. RStudio has been certified as a B Corporation. This means that our open-source mission has been codified in our charter. Our professional software products are enterprise-ready and provide a modular platform that allows teams to adopt open-source data sciences at scale.

Dash & Dash Enterprise allow you to build and deploy analytic web applications using Python, R, or Julia. No JavaScript or DevOps are required. The world's most successful companies offer AI, ML and Python analytics at a fraction of the cost of full-stack development. Dash is the way they do it. Apps and dashboards that run advanced analytics such as NLP, forecasting and computer vision can be delivered. You can work in Python, R, or Julia. Reduce costs by migrating legacy per-seat license software to Dash Enterprise's unlimited end-user pricing model. You can deploy and update Dash apps faster without an IT or DevOps staff. You can create pixel-perfect web apps and dashboards without having to write any CSS. Kubernetes makes it easy to scale. High availability support for mission-critical Python apps

Trino is an engine that runs at incredible speeds. Fast-distributed SQL engine for big data analytics. Helps you explore the data universe. Trino is an extremely parallel and distributed query-engine, which is built from scratch for efficient, low latency analytics. Trino is used by the largest organizations to query data lakes with exabytes of data and massive data warehouses. Supports a wide range of use cases including interactive ad-hoc analysis, large batch queries that take hours to complete, and high volume apps that execute sub-second queries. Trino is a ANSI SQL query engine that works with BI Tools such as R Tableau Power BI Superset and many others. You can natively search data in Hadoop S3, Cassandra MySQL and many other systems without having to use complex, slow and error-prone copying processes. Access data from multiple systems in a single query.

Aqua Data Studio is a tool for database administrators and database developers. It also helps data and business analysts manage data platforms and analyze data visually. It offers a unique combination, unlike its competitors, of a full-featured database editor and visual analytics. It also supports flexible import and export, advanced SQL queries optimization, extensive comparisons of databases and data, as well as powerful team collaboration.

Datalore is a platform for collaborative data science and analytics that aims to improve the entire analytics workflow and make working with data more enjoyable for both data scientists as well as data-savvy business teams. Datalore is a collaborative platform that focuses on data teams workflow. It offers technical-savvy business users the opportunity to work with data teams using no-code and low-code, as well as the power of Jupyter Notebooks. Datalore allows business users to perform analytic self-service. They can work with data using SQL or no-code cells, create reports, and dive deep into data. It allows core data teams to focus on simpler tasks. Datalore allows data scientists and analysts to share their results with ML Engineers. You can share your code with ML Engineers on powerful CPUs and GPUs, and you can collaborate with your colleagues in real time.

Mage transforms data into predictions. In minutes, you can build, train, then deploy predictive models. No AI experience necessary. You can increase user engagement by ranking content in your user's homefeed. Conversion can be increased by showing users the most relevant products to purchase. You can predict which users will quit using your app to increase retention. Matching users in a marketplace can increase conversion. Data is the most crucial part of building AI. Mage will help you navigate this process and offer suggestions on how to improve data. You will become an AI expert. AI and its predictions can be confusing. Mage will explain every metric in detail, showing you how your AI model thinks. With just a few lines code, you can get real-time predictions. Mage makes it easy to integrate your AI model into any application.

Meteomatics is a company that offers a wide range of weather-related services, including high-resolution commercial weather forecasting, power output forecasting for wind, solar and hydro, weather data gathering from the lower atmosphere using Meteodrones, and weather data delivery via the Weather API. Some of the key features of their Weather API include: - Unlimited accesses/day - Weather data querying via URL - Unified weather data access for historical and current weather, forecasts, climate models, and data from over 25 weather models - WMS and WFS interface - Delivery of forecasts with an average response time of 20 to 30 ms - 90 m downscaling worldwide - 1800+ parameters - Historical weather data from 1979 Climate data including climate scenarios up to the year 2100 - Secured use with HTTP and HTTPS - Integration with many formats, connectors, and programming languages available - Proprietary European Weather Model with 1 km resolution – EURO1k (Business plan)

EngineRoom is a powerful tool for process improvement. EngineRoom combines graphical tools, statistical tools, and modeling to organize and manage your projects. Analyze data, manage projects and map and model processes. EngineRoom's intuitive drag and drop interface allows you to avoid the steep learning curve associated with desktop data analysis software. EngineRoom has interactive, patented wizards that guide you through the process of analyzing your data and reporting your results. You can get started instantly without having to install anything on your client's desktop, manage complex licensing files or dedicate hard drive storage. Sign in to your account and you can access your projects from any browser. Your data and results will be saved the same way when you return to a project from anywhere.

The enterprise database for time series, documents, and vectors. Store any type data and combine the simplicity and scalability NoSQL with SQL. CrateDB is a distributed database that runs queries in milliseconds regardless of the complexity, volume, and velocity.

Visplore makes the analysis of large, dirty time series data intuitive and extremely efficient. For process experts, R&D engineers, quality managers, industry consultants, and everyone who has spent a lot of time on the tedious preparation of complex measurement data. Knowing your data is the fundament of unlocking its value. Visplore offers ready-to-use tools to understand correlations, patterns, trends and much more, faster than ever. Cleansing and annotating make the difference between valuable and useless data. In Visplore, you deal with dirty data like outliers, anomalies and process changes as easily as using a drawing program. Integrations with Python, R, Matlab and many other sources makes workflow integration straightforward. And all of that at a performance that is still fun even with millions of data records, and allows for unexpectedly creative analyses.

Displayr is a powerful software for analysis and reporting of survey data. The only tool that you will ever need to uncover data stories and share them. Displayr is a single app that connects your survey data, analyses, visualizations, reports, and reports to provide seamless automation and better insights. Displayr replaces all your complex analysis and reporting tools. Amazing things happen. You can do everything in a fraction the time. From data cleaning, to analysis, to dashboards and presentations. Displayr does all the grunt work, and it's also faster & easier for you to do advanced analysis. Share interactive reports with auto-updating data and analysis. When you combine all your analysis with reporting, you leave yourself less room for errors. If a mistake is found, you can fix it and auto-update all your reports.

Alibaba Cloud launched DataWorks, a Big Data platform product. It offers Big Data development, data permission management and offline job scheduling. DataWorks is easy to use and does not require any special cluster setup or management. To create a workflow, drag and drop nodes. Online editing and debugging of code is possible. You can also ask other developers to join your project. Data integration, MaxCompute SQL and MaxCompute MS, machine learning, shell tasks, and MaxCompute MR are supported. To prevent service interruptions, task monitoring is supported. It sends alarms when errors are detected. It can run millions of tasks simultaneously and supports hourly, daily and weekly schedules. DataWorks is the best platform to build big data warehouses. It also offers comprehensive data warehousing and support services. DataWorks offers a complete solution for data aggregation and processing, as well as data governance and data services.

With a single keystroke, switch between editor and command modes. Use the arrow keys to navigate between cells. All the Jupyter shortcuts are available. Fully interactive outputs are available right under the cell. Editing code cells is easy with smart code completion, quick error checking and quick fixes, and easy navigation. You can connect to remote JupyterHub or JupyterLab servers from the IDE. Interactively run Python scripts and arbitrary expressions in a Python Console. You can see the outputs and the state variables in real time. Split Python scripts into code cells using the #%% separator, and run them individually in a Jupyter notebook. Interactive controls allow you to browse DataFrames or visualizations in real time. All popular Python scientific libraries, including Plotly and Altair, ipywidgets and others, are supported.

With a fully automated cloud infrastructure, experts can explore data and write stable codes at the same time. Zerve’s data science environment gives data scientists and ML teams a unified workspace to explore, collaborate and build data science & AI project like never before. Zerve provides true language interoperability. Users can use Python, R SQL or Markdown in the same canvas and connect these code blocks. Zerve offers unlimited parallelization, allowing for code blocks and containers to run in parallel at any stage of development. Analysis artifacts can be automatically serialized, stored and preserved. This allows you to change a step without having to rerun previous steps. Selecting compute resources and memory in a fine-grained manner for complex data transformation.

All work can be synced, searched and managed across your data science team. Zepl's powerful search allows you to discover and reuse models, code, and other data. Zepl's enterprise collaboration platform allows you to query data from Snowflake or Athena and then build your models in Python. For enhanced interactions with your data, use dynamic forms and pivoting. Zepl creates new containers every time you open your notebook. This ensures that you have the same image each time your models are run. You can invite your team members to join you in a shared space, and they will be able to work together in real-time. Or they can simply leave comments on a notebook. You can share your work with fine-grained access controls. You can allow others to read, edit, run, and share your work. This will facilitate collaboration and distribution. All notebooks can be saved and versioned automatically. An easy-to-use interface allows you to name, manage, roll back, and roll back all versions. You can also export seamlessly into Github.

ggplot2 allows you to create declarative graphics using The Grammar of Graphics. You provide the data and tell ggplot2 what graphical primitives you want to use. ggplot2 has been around for over 10 years and is used by thousands to create millions of plots. This means that ggplot2 itself is relatively stable. If we do make any changes, it will be to add functions or arguments to existing functions rather than to change the behavior of existing ones. If we do make changes to existing behavior, we will do so for compelling reasons. It is better to start with a systematic introduction to ggplot2 than to read individual documentation pages.

IBM SPSS Modeler, a leading visual data-science and machine-learning (ML) solution, is designed to help enterprises accelerate their time to value through the automation of operational tasks by data scientists. It is used by organizations around the world for data preparation, discovery, predictive analytics and model management and deployment. ML is also used to monetize data assets. IBM SPSS Modeler transforms data in the best possible format for accurate predictive modeling. You can now analyze data in just a few clicks, identify fixes, screen fields out and derive new characteristics. IBM SPSS Modeler uses its powerful graphics engine to help you bring your insights to life. The smart chart recommender will select the best chart from dozens of options to share your insights.

Decentriq is the choice of privacy-conscious organizations. Your data is always under your control with the latest encryption and privacy-enhancing technology, such as synthetic data and differential privacy. Your data is kept private by end-to-end encryption. Decentriq can't see or access your data. Remote attestation allows you to verify that your data has been encrypted and that only approved analyses have been run. Built in partnership with leading hardware and infrastructure providers. The platform is designed to handle advanced AI and machine-learning models. It keeps your data unaccessible, no matter what the challenge. Scalability and data protection don't have be compromised by processing speeds that are comparable to those of the cloud. Our growing network supports more streamlined workflows on leading data platforms.

All your data needs can be met by a powerful platform. From data ingestion/integration, transformation, and storage to knowledge catalog, graph networks, data analytics, governance, monitoring, and, sharing. An AI/ML Platform that allows enterprises to train, test and troubleshoot models, deploy them, and govern them at scale. This will boost productivity, while maintaining model performance with confidence in production. AutoML is a dedicated solution that allows you to train models with minimum effort or CustomML allows you to train your own case-specific models. You can now connect ML logic with data. Integrating your protocols and authorization models with an integrated exploration of possible action. Extreme configurability is at your disposal. Use internal lineage system for alerting and impact analyses. Interwoven with security paradigm; provides unalterable tracking

The smart semantic layer unifies metrics and speeds up the delivery of data products by 90% with shorter SQL queries. Model data using business terms for a common meaning and to align business metrics. Define semantic relationships to replace JOINs, making queries much easier. Hierarchies and classifications can help you better understand data. Automatically map data into the semantic model. Join multiple data sources using a powerful SQL engine distributed to query data at a large scale. Consume data in the form of a semantically connected graph. Materialized views and an intelligent cache engine can boost performance and reduce compute costs. Advanced query optimizations are available. Connect to any file format, cloud, datalake, data warehouse, or database. Timbr allows you to work seamlessly with your data sources. Timbr optimizes a query and pushes it to the backend when a query is executed.

Betteromics is deployed in your VPC as a Private SaaS so you can make connections with all your data. Validate structured and unstructured information using configurable rules. You can audit and trace your data from the input to the analysis, with full data provenance. Use large language models and natural language processing to abstract data elements for QC, labeling and analysis. Develop and tune models quickly to fit your task/data. Detect anomalies, make predictive, understand your data and optimize your processes. Public datasets that are ready for integration can enhance and complement your analysis. Clinical-grade security, including full encryption, data tracability, and role based access controls.