Alternatives to Wolfram|One

BigQuery is a serverless, multicloud data warehouse that makes working with all types of data effortless, allowing you to focus on extracting valuable business insights quickly. As a central component of Google’s data cloud, it streamlines data integration, enables cost-effective and secure scaling of analytics, and offers built-in business intelligence for sharing detailed data insights. With a simple SQL interface, it also supports training and deploying machine learning models, helping to foster data-driven decision-making across your organization. Its robust performance ensures that businesses can handle increasing data volumes with minimal effort, scaling to meet the needs of growing enterprises. Gemini within BigQuery brings AI-powered tools that enhance collaboration and productivity, such as code recommendations, visual data preparation, and intelligent suggestions aimed at improving efficiency and lowering costs. The platform offers an all-in-one environment with SQL, a notebook, and a natural language-based canvas interface, catering to data professionals of all skill levels. This cohesive workspace simplifies the entire analytics journey, enabling teams to work faster and more efficiently.

Qloo, the "Cultural AI", is capable of decoding and forecasting consumer tastes around the world. Privacy-first API that predicts global consumer preferences, catalogs hundreds of million of cultural entities, and is privacy-first. Our API provides contextualized personalization and insight based on deep understanding of consumer behavior. We have access to more than 575,000,000 people, places, and things. Our technology allows you to see beyond trends and discover the connections that underlie people's tastes in their world. Our vast library includes entities such as brands, music, film and fashion. We also have information about notable people. Results are delivered in milliseconds. They can be weighted with factors like regionalization and real time popularity. Companies who want to use best-in-class data to enhance their customer experiences. Our flagship recommendation API provides results based on demographics and preferences, cultural entities, metadata, geolocational factors, and metadata.

At Posit, we strive to enhance data science by making it more open, user-friendly, accessible, and collaborative for everyone. Our suite of tools empowers individuals, teams, and enterprises to utilize advanced analytics to derive meaningful insights and create a significant impact. From our inception, we have committed to open-source software, such as RStudio IDE, Shiny, and tidyverse, because we firmly believe in democratizing access to data science tools. We offer R and Python-based solutions designed to streamline the analysis process, enabling you to achieve higher-quality results in less time. Our platform facilitates secure sharing of data-science applications across your organization, reinforcing the idea that our code belongs to you. You can build upon it, share it, and use it to enhance the lives of others. By simplifying the processes of uploading, storing, accessing, and distributing your work, we aim to make your experience seamless. We are always excited to learn about the incredible projects being developed using our tools globally, and we cherish the opportunity to share those inspiring stories with the community. Ultimately, our mission is to foster a vibrant ecosystem where data science can flourish for everyone involved.

IBM® SPSS® Statistics software is used by a variety of customers to solve industry-specific business issues to drive quality decision-making. The IBM® SPSS® software platform offers advanced statistical analysis, a vast library of machine learning algorithms, text analysis, open-source extensibility, integration with big data and seamless deployment into applications. Its ease of use, flexibility and scalability make SPSS accessible to users of all skill levels. What’s more, it’s suitable for projects of all sizes and levels of complexity, and can help you find new opportunities, improve efficiency and minimize risk.

We adhere to the principles of offering a computational framework. The Wolfram Language delivers an unprecedented level of computing power, utilizing a sophisticated blend of computational intelligence derived from diverse algorithms and extensive real-world insights, meticulously curated over thirty years. It is designed to be adaptable for projects of any size, supporting seamless deployment both locally and in cloud environments. Furthermore, the Wolfram Language is grounded in clear foundational principles and a cohesive symbolic structure, establishing itself as one of the most efficient programming languages available today, as well as the first genuine computational communication language that facilitates interaction between humans and artificial intelligence. This evolution represents a significant leap forward in the way we engage with technology and solve complex problems.

The Wolfram Data Science Platform provides the ability to work with both structured and unstructured data, whether it is static or streaming in real-time. By leveraging the capabilities of WDF alongside the same linguistic framework found in Wolfram|Alpha, users can transform unstructured data into a structured format through either automated processes or guided assistance for disambiguation and destructuring. This platform employs advanced database connection technologies to integrate content from various databases into its versatile symbolic representation. Able to natively interpret hundreds of data formats, the Wolfram Data Science Platform facilitates conversion across diverse data types. It accommodates a wide range of data types, including images, text, networks, geometry, sounds, and GIS data, among others. Utilizing the innovative symbolic data representation inherent in the Wolfram Language, the platform can effortlessly manage both SQL-style and NoSQL data structures. Additionally, the Wolfram Data Science Platform automatically generates a comprehensive interactive report, applying algorithms that identify and visualize key features of the dataset, making data analysis more intuitive and informative. This feature-rich environment empowers users to extract deeper insights from their data effectively.

The launch of Wolfram Alpha established a groundbreaking approach to acquiring knowledge and finding answers—not by merely browsing the internet, but by performing real-time computations using a rich array of integrated data, algorithms, and methodologies. This innovative tool democratizes expert-level insight and functionality for individuals across various fields and educational backgrounds. Our goal is to accommodate entirely free-form queries while functioning as a knowledge engine that produces impactful results presented with utmost clarity. The realization of Wolfram Alpha hinges on a distinctive combination of factors, propelled by the visionary leadership of Stephen Wolfram. For the first time in history, the computational power available is sufficient to support the extensive capabilities of Wolfram Alpha, complemented by the internet as a widespread medium for access. However, the mere existence of this technology was not solely sufficient to make Wolfram Alpha a reality; it required a unique vision and relentless commitment to innovation as well.

Create and resolve intricate optimization models to determine the most effective strategies. IBM® ILOG® CPLEX® Optimization Studio leverages decision optimization technology to enhance your business choices, allowing for swift model development and deployment while crafting practical applications that can markedly boost business performance. How does it achieve this? This platform serves as a prescriptive analytics tool that facilitates the quick creation and implementation of decision optimization models utilizing mathematical and constraint programming techniques. It features a comprehensive integrated development environment that supports Optimization Programming Language (OPL) along with the powerful CPLEX and CP Optimizer solvers. Essentially, it transforms data science into actionable decisions. Additionally, IBM Decision Optimization is incorporated within Cloud Pak for Data, enabling the fusion of optimization and machine learning within a cohesive framework, IBM Watson® Studio, which offers capabilities for AI-enhanced optimization modeling. This combination not only accelerates decision-making but also optimizes operational efficiency across various business sectors.

The largest team in the world specializing in Functional Programming and Fast Data engineers is dedicated to crafting tailored, high-performance solutions. Our approach transitions ideas into tangible outcomes through swift prototyping and concept validation. We establish a robust ecosystem that facilitates large-scale delivery through continuous integration and deployment, aligning with your specific needs. By comprehending strategic objectives and the requirements of stakeholders, we foster a unified vision. We aim to efficiently deploy minimum viable products (MVPs) to expedite product launches, ensuring an effective approach. Our commitment to ongoing enhancements allows us to adapt to emerging requirements seamlessly. The creation of exceptional products and the provision of unparalleled engineering services are made possible by leveraging cutting-edge tools and technologies. We empower you to seize opportunities, tackle competitive challenges, and effectively scale your successful investments by minimizing friction within your organizational structures, processes, and culture. Knoldus collaborates with clients to uncover and harness significant value and insights from data while also ensuring the adaptability and responsiveness of their strategies in a rapidly changing market.

Appsilon specializes in cutting-edge data analytics, machine learning, and managed service solutions tailored for Fortune 500 companies, non-governmental organizations, and non-profits. We excel in creating the most sophisticated R Shiny applications, enabling us to efficiently develop and expand enterprise-level Shiny dashboards. Our custom machine learning frameworks empower us to deliver prototypes for Computer Vision, Natural Language Processing, and fraud detection in just a week. Above all, our mission is to make a meaningful difference in the world. Through our AI For Good Initiative, we actively apply our expertise to initiatives that enhance human safety and support the conservation of wildlife across the globe. Recently, our efforts have included using computer vision to combat poaching in Africa, conducting satellite image analyses to evaluate damage from natural disasters, and developing tools for assessing COVID-19 risks. Additionally, Appsilon takes pride in being at the forefront of open-source innovation, fostering collaboration and transparency in technology development. Our commitment to these values positions us as leaders in both ethical practices and technological advancements.

Mathematica represents the ultimate solution for contemporary technical computing. Over the past thirty years, it has set the benchmark for excellence in this field, serving as the primary computational framework for countless innovators, educators, students, and various professionals globally. Renowned for its impressive technical capabilities and user-friendly interface, Mathematica offers a unified, ever-evolving system that encompasses the full spectrum of technical computing. This powerful tool is conveniently accessible via any web browser in the cloud and is also available on all current desktop platforms. With a vibrant development process and a clear vision maintained for three decades, Mathematica distinguishes itself across numerous aspects, showcasing its unmatched support for the evolving needs of today’s technical computing environments and workflows, while continuing to adapt and grow with the demands of its users.

Experience an enterprise-level architecture and a cloud data platform powered by Snowflake® that enables secure storage and utilization of your data in the cloud. With integrated ETL and an intuitive drag-and-drop visual workflow designer, you can easily connect, clean, and transform data from over 250 sources. Harness cutting-edge Search and AI technology to quickly generate insights and actionable analytics from your data within seconds. Utilize our advanced AI/ML environments to create, refine, and deploy your predictive analytics and forecasting models. Take your data capabilities further with our comprehensive AI/ML frameworks, allowing you to design, train, and implement AI models through the PurpleCube Data Science module. Additionally, construct engaging BI visualizations with PurpleCube Analytics, explore your data using natural language searches, and benefit from AI-driven insights and intelligent recommendations that reveal answers to questions you may not have considered. This holistic approach ensures that you are equipped to make data-driven decisions with confidence and clarity.

Oversee and protect the entire data lifecycle from the Edge to AI across any cloud platform or data center. Functions seamlessly within all leading public cloud services as well as private clouds, providing a uniform public cloud experience universally. Unifies data management and analytical processes throughout the data lifecycle, enabling access to data from any location. Ensures the implementation of security measures, regulatory compliance, migration strategies, and metadata management in every environment. With a focus on open source, adaptable integrations, and compatibility with various data storage and computing systems, it enhances the accessibility of self-service analytics. This enables users to engage in integrated, multifunctional analytics on well-managed and protected business data, while ensuring a consistent experience across on-premises, hybrid, and multi-cloud settings. Benefit from standardized data security, governance, lineage tracking, and control, all while delivering the robust and user-friendly cloud analytics solutions that business users need, effectively reducing the reliance on unauthorized IT solutions. Additionally, these capabilities foster a collaborative environment where data-driven decision-making is streamlined and more efficient.

Stata delivers everything you need for reproducible data analysis—powerful statistics, visualization, data manipulation, and automated reporting—all in one intuitive platform. Stata is quick and accurate. The extensive graphical interface makes it easy to use, but is also fully programable. Stata's menus, dialogs and buttons give you the best of both worlds. All Stata's data management, statistical, and graphical features are easy to access by dragging and dropping or point-and-click. To quickly execute commands, you can use Stata's intuitive command syntax. You can log all actions and results, regardless of whether you use the menus or dialogs. This will ensure reproducibility and integrity in your analysis. Stata also offers complete command-line programming and programming capabilities, including a full matrix language. All the commands that Stata ships with are available to you, whether you want to create new Stata commands or script your analysis.

Create and execute data-heavy projects using the user-friendly, open-source Metaflow framework. The Outerbounds platform offers a completely managed environment to run, scale, and deploy these projects with reliability. It serves as a comprehensive solution for all your machine learning and data science endeavors. You can securely access data from your current data warehouses and utilize a computing cluster that is tailored for both scalability and cost-effectiveness. With 24/7 managed orchestration, production workflows are streamlined and efficient. Results can be leveraged to enhance any application, empowering your data scientists while receiving approval from engineers. The Outerbounds Platform enables rapid development, large-scale experimentation, and confident production deployment, all while adhering to the policies set by your engineers and operating securely within your cloud account. Security is fundamentally integrated into our platform rather than being an afterthought. It meets your compliance needs through various layers of security measures, including centralized authentication, a strict permission framework, and clearly defined roles for task execution, ensuring that your data and processes remain safe. This cohesive structure allows teams to collaborate effectively while maintaining control over their data environment.

Amadea technology boasts the industry's quickest real-time calculation and modeling engine, enabling accelerated development, deployment, and automation of analytics projects within a unified platform. The key to successful analytical initiatives lies in data quality, and with the ISoft real-time calculation engine, Amadea empowers organizations to handle vast and intricate datasets instantly, regardless of size. ISoft's inception stemmed from the understanding that effective analytical projects require active participation from business users at every phase. Built on a no-code interface that is user-friendly for everyone, Amadea encourages all stakeholders in analytical endeavors to contribute meaningfully. With the unmatched speed of its real-time calculation capabilities, Amadea allows for the simultaneous specification, prototyping, and construction of data applications. Furthermore, the platform is capable of executing standard calculations at an impressive rate of 10 million lines per second per core, solidifying its position as the fastest real-time data analysis engine available today. Therefore, leveraging Amadea can significantly enhance the efficiency and effectiveness of your analytics projects.

Introducing the world’s pioneering end-to-end platform designed for all your AI-driven innovation requirements—from data cleansing and organization to the creation and deployment of sophisticated data science models, as well as the integration of advanced analytics algorithms featuring built-in Recommendation AI; our platform also simplifies outcome interpretation with intuitive visualization dashboards and employs Explainable AI to trace the origins of outcomes. FutureAnalytica delivers a comprehensive, seamless data science journey, equipped with essential attributes such as a powerful Data Lakehouse, an innovative AI Studio, an inclusive AI Marketplace, and a top-notch data science support team available as needed. This unique platform is specifically tailored to streamline your efforts, reduce costs, and save time throughout your data science and AI endeavors. Start by engaging with our leadership team, and expect a swift technology evaluation within just 1 to 3 days. In a span of 10 to 18 days, you can construct fully automated, ready-to-integrate AI solutions using FutureAnalytica’s advanced platform, paving the way for a transformative approach to data management and analysis. Embrace the future of AI innovation with us today!

No matter what your business requirements are, quickly unearth concealed insights with HyperCube, a platform tailored to meet the needs of data scientists. Harness your business data effectively to gain clarity, identify untapped opportunities, make forecasts, and mitigate risks before they arise. HyperCube transforms vast amounts of data into practical insights. Whether you're just starting with analytics or are a seasoned machine learning specialist, HyperCube is thoughtfully crafted to cater to your needs. It serves as the multifaceted tool of data science, integrating both proprietary and open-source code to provide a diverse array of data analysis capabilities, available either as ready-to-use applications or tailored business solutions. We are committed to continuously enhancing our technology to offer you the most cutting-edge, user-friendly, and flexible outcomes. You can choose from a variety of applications, data-as-a-service (DaaS), and tailored solutions for specific industries, ensuring that your unique requirements are met efficiently. With HyperCube, unlocking the full potential of your data has never been more accessible.

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

By utilizing a drag-and-drop feature from an extensive range of both built-in and expandable modeling libraries, you can create robust, multidomain models that represent your entire system. The integration of the Wolfram Language enhances this experience by providing a comprehensive environment for the analysis, comprehension, and rapid iteration of system designs, ultimately driving insight, innovation, and tangible outcomes. In reality, machines and systems seldom fit neatly into a single physical domain; instead, models can incorporate various interlinked components from multiple domains that reflect real-world configurations. Immediate exploration is facilitated, allowing you to access all component values in your model with just a click. You can delve into specific areas of interest and select from a variety of built-in plotting styles through a user-friendly point-and-click interface. Additionally, you have the capability to conduct your own symbolic and numerical analyses by tapping into the complete set of model equations and simulation outcomes. This powerful combination brings the full potential of the Wolfram Language into your model analysis, making it an invaluable tool for engineers and designers. Furthermore, the ability to seamlessly transition between different domains within your model fosters a deeper understanding of complex systems.

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.

Experience the power of advanced computing right at your fingertips. With the capabilities of parallel computing and innovative algorithms, there's no reason to hesitate any longer. Created specifically for data scientists in the business realm, this all-inclusive time-series platform delivers the fastest computing available. Shapelets offers a suite of analytical tools, including causality analysis, discord detection, motif discovery, forecasting, and clustering, among others. You can also run, expand, and incorporate your own algorithms into the Shapelets platform, maximizing the potential of Big Data analysis. Seamlessly integrating with various data collection and storage systems, Shapelets ensures compatibility with MS Office and other visualization tools, making it easy to share insights without requiring extensive technical knowledge. Our user interface collaborates with the server to provide interactive visualizations, allowing you to fully leverage your metadata and display it through a variety of modern graphical representations. Additionally, Shapelets equips professionals in the oil, gas, and energy sectors to conduct real-time analyses of their operational data, enhancing decision-making and operational efficiency. By utilizing Shapelets, you can transform complex data into actionable insights.

A platform for Machine Learning and Predictive Analytics enhances data-driven decision-making and propels business growth through sophisticated artificial intelligence within an integrated machine learning and big data analytics framework. OpenText Magellan leverages AI technologies to deliver predictive analytics through user-friendly and adaptable data visualizations that enhance the utility of business intelligence. The implementation of artificial intelligence software streamlines the big data processing task, providing essential business insights in a format that aligns with the organization’s most significant goals. By enriching business operations with a tailored combination of features such as predictive modeling, data exploration tools, data mining methods, and IoT data analytics, companies can effectively utilize their data to refine their decision-making processes based on actionable business intelligence and analytics. This comprehensive approach not only improves operational efficiency but also fosters a culture of data-driven innovation within the organization.

SAS® Viya® offers a robust and scalable analytics platform that is both efficient and easy to implement, allowing organizations to address a variety of business challenges. The insights generated automatically help in pinpointing the most frequently used variables across all models, highlighting key variables selected along with evaluation outcomes for each model. With the integration of natural language generation, project summaries are produced in straightforward language, which simplifies the interpretation of reports for users. Moreover, members of the analytics team can enhance the insights report with project notes, promoting better communication and teamwork. SAS further enables the integration of open source code within analyses, allowing users to utilize open source algorithms effortlessly in its platform. This flexibility encourages collaboration throughout your organization, as users are free to program in their preferred language. Additionally, you can leverage SAS Deep Learning with Python (DLPy), an open-source package available on GitHub, to expand your analytical capabilities even further. By using these tools, businesses can significantly enhance their data-driven decision-making processes.

Enhance the transition of machine learning from theoretical research to practical application with a seamless experience tailored for your conventional platform. Cloudera Data Science Workbench (CDSW) offers a user-friendly environment for data scientists, allowing them to work with Python, R, and Scala right in their web browsers. Users can download and explore the newest libraries and frameworks within customizable project settings that mirror the functionality of their local machines. CDSW ensures robust connectivity not only to CDH and HDP but also to the essential systems that support your data science teams in their analytical endeavors. Furthermore, Cloudera Data Science Workbench empowers data scientists to oversee their analytics pipelines independently, featuring integrated scheduling, monitoring, and email notifications. This platform enables rapid development and prototyping of innovative machine learning initiatives while simplifying the deployment process into a production environment. By streamlining these workflows, teams can focus on delivering impactful results more efficiently.

A cloud-based data science platform provides meticulously curated and refined data, primed for immediate use. Companies encounter considerable hurdles, limited resources, and elevated expenses when handling their data before they can extract any meaningful insights. The data undergoes a process of ingestion, cleansing, storage, and access, culminating in analysis, which is where true value is derived. Our solution empowers clients to concentrate on their primary business functions instead of the costly, resource-intensive data lifecycle, as we manage those complexities for them. Additionally, our cloud-native platform supports real-time streaming analytics, capitalizing on the advantages of cloud architecture, allowing INQDATA to deliver swift and scalable access to both historical and real-time data while eliminating infrastructure complexities. This approach not only enhances efficiency but also ensures that businesses can adapt quickly to their evolving data needs.

MATLAB® offers a desktop environment specifically optimized for iterative design and analysis, paired with a programming language that allows for straightforward expression of matrix and array mathematics. It features the Live Editor, which enables users to create scripts that merge code, output, and formatted text within an interactive notebook. The toolboxes provided by MATLAB are meticulously developed, thoroughly tested, and comprehensively documented. Additionally, MATLAB applications allow users to visualize how various algorithms interact with their data. You can refine your results through repeated iterations and then easily generate a MATLAB program to replicate or automate your processes. The platform also allows for scaling analyses across clusters, GPUs, and cloud environments with minimal modifications to your existing code. There is no need to overhaul your programming practices or master complex big data techniques. You can automatically convert MATLAB algorithms into C/C++, HDL, and CUDA code, enabling execution on embedded processors or FPGA/ASIC systems. Furthermore, when used in conjunction with Simulink, MATLAB enhances the support for Model-Based Design methodologies, making it a versatile tool for engineers and researchers alike. This adaptability makes MATLAB an essential resource for tackling a wide range of computational challenges.

The primary obstacle in expanding AI-driven decision-making lies in the underutilization of data. IBM Cloud Pak® for Data provides a cohesive platform that integrates a data fabric, enabling seamless connection and access to isolated data, whether it resides on-premises or in various cloud environments, without necessitating data relocation. It streamlines data accessibility by automatically identifying and organizing data to present actionable knowledge assets to users, while simultaneously implementing automated policy enforcement to ensure secure usage. To further enhance the speed of insights, this platform incorporates a modern cloud data warehouse that works in harmony with existing systems. It universally enforces data privacy and usage policies across all datasets, ensuring compliance is maintained. By leveraging a high-performance cloud data warehouse, organizations can obtain insights more rapidly. Additionally, the platform empowers data scientists, developers, and analysts with a comprehensive interface to construct, deploy, and manage reliable AI models across any cloud infrastructure. Moreover, enhance your analytics capabilities with Netezza, a robust data warehouse designed for high performance and efficiency. This comprehensive approach not only accelerates decision-making but also fosters innovation across various sectors.

Google Colab is a complimentary, cloud-based Jupyter Notebook platform that facilitates environments for machine learning, data analysis, and educational initiatives. It provides users with immediate access to powerful computational resources, including GPUs and TPUs, without the need for complex setup, making it particularly suitable for those engaged in data-heavy projects. Users can execute Python code in an interactive notebook format, collaborate seamlessly on various projects, and utilize a wide range of pre-built tools to enhance their experimentation and learning experience. Additionally, Colab has introduced a Data Science Agent that streamlines the analytical process by automating tasks from data comprehension to providing insights within a functional Colab notebook, although it is important to note that the agent may produce errors. This innovative feature further supports users in efficiently navigating the complexities of data science workflows.

By combining the advantages of a notebook with the functionality of an IDE, experts are empowered to analyze data while simultaneously developing reliable code, all supported by a fully automated cloud infrastructure. Zerve revolutionizes the data science development environment, providing teams focused on data science and machine learning with a cohesive platform to explore, collaborate, construct, and deploy their AI projects like never before. This innovative tool ensures true language interoperability, allowing users to seamlessly integrate Python, R, SQL, or Markdown within the same workspace, facilitating the connection of various code blocks. Zerve eliminates the frustrations of lengthy code execution or cumbersome containers by enabling unlimited parallel processing throughout the entire development process. Furthermore, artifacts generated during analysis are automatically serialized, versioned, stored, and preserved, making it simple to modify any step in the data pipeline without the need to reprocess earlier stages. Users also benefit from precise control over computing resources and additional memory, which is essential for handling intricate data transformations. With Zerve, data science teams can enhance their workflow efficiency and streamline project management significantly.

Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence. Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs. Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500 companies, such as United, Kroger, Philips, Truist, and many others.

Machine learning reveals concealed patterns and valuable insights within enterprise data, ultimately adding significant value to businesses. Oracle Machine Learning streamlines the process of creating and deploying machine learning models for data scientists by minimizing data movement, incorporating AutoML technology, and facilitating easier deployment. Productivity for data scientists and developers is enhanced while the learning curve is shortened through the use of user-friendly Apache Zeppelin notebook technology based on open source. These notebooks accommodate SQL, PL/SQL, Python, and markdown interpreters tailored for Oracle Autonomous Database, enabling users to utilize their preferred programming languages when building models. Additionally, a no-code interface that leverages AutoML on Autonomous Database enhances accessibility for both data scientists and non-expert users, allowing them to harness powerful in-database algorithms for tasks like classification and regression. Furthermore, data scientists benefit from seamless model deployment through the integrated Oracle Machine Learning AutoML User Interface, ensuring a smoother transition from model development to application. This comprehensive approach not only boosts efficiency but also democratizes machine learning capabilities across the organization.

Enhance your scientific research and equip your R&D team with unified data in the cloud. The Tetra R&D Data Cloud merges the only cloud-native data platform specifically designed for global pharmaceutical enterprises with the expansive and rapidly growing network of Life Sciences integrations and extensive industry expertise, providing a robust solution for leveraging your most critical asset: R&D data. This platform encompasses the entire life-cycle of your R&D data, facilitating processes from acquisition to harmonization, engineering, and subsequent analysis while offering native compatibility with cutting-edge data science tools. It supports a vendor-agnostic approach with pre-existing integrations that allow seamless connectivity to instruments, analytics and informatics applications, as well as ELN/LIMS and CRO/CDMOs. By consolidating data acquisition, management, harmonization, integration/engineering, and data science enablement into one comprehensive platform, it simplifies the complexities of R&D operations. This holistic approach not only streamlines workflows but also unlocks new possibilities for innovation and discovery.

Predictive modeling utilizing machine learning and explainable AI is revolutionized by FICO® Analytics Workbench™, a comprehensive collection of advanced analytic authoring tools that enables organizations to enhance their business decisions throughout the customer journey. This platform allows data scientists to develop exceptional decision-making abilities by leveraging an extensive variety of predictive modeling tools and algorithms, incorporating cutting-edge machine learning and explainable AI techniques. By merging the strengths of open-source data science with FICO's proprietary innovations, we provide unparalleled analytic capabilities to uncover, integrate, and implement predictive insights from data. Additionally, the Analytics Workbench is constructed on the robust FICO® Platform, facilitating the seamless deployment of new predictive models and strategies into operational environments, thereby driving efficiency and effectiveness in business processes. Ultimately, this empowers companies to make informed, data-driven decisions that can significantly impact their success.

SAP Analytics Cloud is a data visualization and business intelligence platform that helps businesses of all sizes make better decisions. SAP Analytics Cloud features include digital boardroom, predictive analytics, business planning, reporting, and digital boardroom. SAP Analytics Cloud can be deployed in the cloud and is accessible via iPhones or iPads. SAP Analytics Cloud offers multiple support options, including online support, phone support, and knowledge base.

Doolytic is at the forefront of big data discovery, integrating data exploration, advanced analytics, and the vast potential of big data. The company is empowering skilled BI users to participate in a transformative movement toward self-service big data exploration, uncovering the inherent data scientist within everyone. As an enterprise software solution, doolytic offers native discovery capabilities specifically designed for big data environments. Built on cutting-edge, scalable, open-source technologies, doolytic ensures lightning-fast performance, managing billions of records and petabytes of information seamlessly. It handles structured, unstructured, and real-time data from diverse sources, providing sophisticated query capabilities tailored for expert users while integrating with R for advanced analytics and predictive modeling. Users can effortlessly search, analyze, and visualize data from any format and source in real-time, thanks to the flexible architecture of Elastic. By harnessing the capabilities of Hadoop data lakes, doolytic eliminates latency and concurrency challenges, addressing common BI issues and facilitating big data discovery without cumbersome or inefficient alternatives. With doolytic, organizations can truly unlock the full potential of their data assets.

Develop, implement, and manage data-driven decision-making processes on a large scale in either real-time or batch modes. SAS Data Science Programming caters to data scientists who prefer a purely programmatic method, allowing them to utilize SAS's analytical tools throughout the entire analytics life cycle, which encompasses data preparation, exploration, and deployment. Uncover and visualize significant patterns within your datasets, enabling the creation and dissemination of interactive reports and dashboards. Additionally, leverage self-service analytics to swiftly evaluate likely outcomes, leading to more informed and data-centric decisions. Engage with your data and create or modify predictive analytical models using the SAS® Viya® platform. This collaborative environment empowers data scientists, statisticians, and analysts to work together, refining their models iteratively for various segments, ultimately supporting decision-making based on reliable insights. Tackle intricate analytical challenges through an all-encompassing visual interface that efficiently manages every aspect of the analytics life cycle, ensuring that users can navigate complexities with ease and precision. By embracing this approach, organizations can enhance their strategic decision-making capabilities significantly.

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.

The RAPIDS software library suite, designed on CUDA-X AI, empowers users to run comprehensive data science and analytics workflows entirely on GPUs. It utilizes NVIDIA® CUDA® primitives for optimizing low-level computations while providing user-friendly Python interfaces that leverage GPU parallelism and high-speed memory access. Additionally, RAPIDS emphasizes essential data preparation processes tailored for analytics and data science, featuring a familiar DataFrame API that seamlessly integrates with various machine learning algorithms to enhance pipeline efficiency without incurring the usual serialization overhead. Moreover, it supports multi-node and multi-GPU setups, enabling significantly faster processing and training on considerably larger datasets. By incorporating RAPIDS, you can enhance your Python data science workflows with minimal code modifications and without the need to learn any new tools. This approach not only streamlines the model iteration process but also facilitates more frequent deployments, ultimately leading to improved machine learning model accuracy. As a result, RAPIDS significantly transforms the landscape of data science, making it more efficient and accessible.

Incorporate analytics into immediate interactions and event-driven functionalities. The SAS Visual Data Science Decisioning suite offers strong capabilities in data management, visualization, advanced analytics, and model oversight. It enhances decision-making by crafting, integrating, and governing analytically driven decision processes at scale, whether in real-time or through batch processing. Additionally, it facilitates analytics deployment in the data stream to uncover valuable insights. Tackle intricate analytical challenges with an intuitive visual interface that manages all stages of the analytics life cycle efficiently. Running on SAS® Viya®, SAS Visual Data Mining and Machine Learning merges data manipulation, exploration, feature development, and cutting-edge statistical, data mining, and machine learning methodologies within a single, scalable in-memory processing framework. Users can access data files, libraries, and existing scripts, or create new ones, via this web-based application that is conveniently accessible through any browser, thus enhancing flexibility and collaboration.

Analysts can leverage drag-and-drop tools alongside generative AI to prepare and blend data up to 100 times faster compared to traditional methods. A self-service data analytics platform empowers every analyst by eliminating costly bottlenecks in the analytics process. Alteryx Designer stands out as a self-service data analytics solution that equips analysts to effectively prepare, blend, and analyze data through user-friendly, drag-and-drop interfaces. The platform boasts compatibility with over 300 automation tools and integrates seamlessly with more than 80 data sources. By prioritizing low-code and no-code features, Alteryx Designer allows users to construct analytic workflows effortlessly, expedite analytical tasks using generative AI, and derive insights without requiring extensive programming knowledge. Additionally, it facilitates the export of results to more than 70 different tools, showcasing its exceptional versatility. Overall, this design enhances operational efficiency, enabling organizations to accelerate their data preparation and analytical processes significantly.

Dask is a freely available open-source library that is developed in collaboration with various community initiatives such as NumPy, pandas, and scikit-learn. It leverages the existing Python APIs and data structures, allowing users to seamlessly transition between NumPy, pandas, and scikit-learn and their Dask-enhanced versions. The schedulers in Dask are capable of scaling across extensive clusters with thousands of nodes, and its algorithms have been validated on some of the most powerful supercomputers globally. However, getting started doesn't require access to a large cluster; Dask includes schedulers tailored for personal computing environments. Many individuals currently utilize Dask to enhance computations on their laptops, taking advantage of multiple processing cores and utilizing disk space for additional storage. Furthermore, Dask provides lower-level APIs that enable the creation of customized systems for internal applications. This functionality is particularly beneficial for open-source innovators looking to parallelize their own software packages, as well as business executives aiming to scale their unique business strategies efficiently. In essence, Dask serves as a versatile tool that bridges the gap between simple local computations and complex distributed processing.

The Databricks Data Intelligence Platform empowers every member of your organization to leverage data and artificial intelligence effectively. Constructed on a lakehouse architecture, it establishes a cohesive and transparent foundation for all aspects of data management and governance, enhanced by a Data Intelligence Engine that recognizes the distinct characteristics of your data. Companies that excel across various sectors will be those that harness the power of data and AI. Covering everything from ETL processes to data warehousing and generative AI, Databricks facilitates the streamlining and acceleration of your data and AI objectives. By merging generative AI with the integrative advantages of a lakehouse, Databricks fuels a Data Intelligence Engine that comprehends the specific semantics of your data. This functionality enables the platform to optimize performance automatically and manage infrastructure in a manner tailored to your organization's needs. Additionally, the Data Intelligence Engine is designed to grasp the unique language of your enterprise, making the search and exploration of new data as straightforward as posing a question to a colleague, thus fostering collaboration and efficiency. Ultimately, this innovative approach transforms the way organizations interact with their data, driving better decision-making and insights.

TrueFoundry is a cloud-native platform-as-a-service for machine learning training and deployment built on Kubernetes, designed to empower machine learning teams to train and launch models with the efficiency and reliability typically associated with major tech companies, all while ensuring scalability to reduce costs and speed up production release. By abstracting the complexities of Kubernetes, it allows data scientists to work in a familiar environment without the overhead of managing infrastructure. Additionally, it facilitates the seamless deployment and fine-tuning of large language models, prioritizing security and cost-effectiveness throughout the process. TrueFoundry features an open-ended, API-driven architecture that integrates smoothly with internal systems, enables deployment on a company's existing infrastructure, and upholds stringent data privacy and DevSecOps standards, ensuring that teams can innovate without compromising on security. This comprehensive approach not only streamlines workflows but also fosters collaboration among teams, ultimately driving faster and more efficient model deployment.

Embrace a groundbreaking age of analytics through the Alteryx AI Platform. Equip your organization with streamlined data preparation, analytics powered by artificial intelligence, and accessible machine learning, all while ensuring governance and security are built in. This marks the dawn of a new era for data-driven decision-making accessible to every user and team at all levels. Enhance your teams' capabilities with a straightforward, user-friendly interface that enables everyone to develop analytical solutions that boost productivity, efficiency, and profitability. Foster a robust analytics culture by utilizing a comprehensive cloud analytics platform that allows you to convert data into meaningful insights via self-service data preparation, machine learning, and AI-generated findings. Minimize risks and safeguard your data with cutting-edge security protocols and certifications. Additionally, seamlessly connect to your data and applications through open API standards, facilitating a more integrated and efficient analytical environment. By adopting these innovations, your organization can thrive in an increasingly data-centric world.

SAS Visual Statistics allows for collaborative data exploration among multiple users, enabling them to interactively develop and refine predictive models. Data scientists and statisticians can leverage the most suitable analytical techniques to act on insights at a detailed level. Consequently, you will discover insights at remarkable speeds, uncovering new opportunities for revenue growth. The platform facilitates the construction and fine-tuning of models aimed at specific demographics or segments while simultaneously running various scenarios. This capability encourages users to pose numerous what-if questions to enhance outcomes. Additionally, results can be operationalized through automatically generated score code. Users are empowered to visually manipulate data by adding or adjusting variables, eliminating outliers, and more. Changes can be instantly assessed for their impact on the model's predictive accuracy, allowing for swift adjustments. Data science teams enjoy the ultimate flexibility by working in their preferred programming languages, maximizing their expertise. Ultimately, SAS Visual Statistics integrates all analytical resources, making it a comprehensive solution for data-driven decision-making. It fosters an environment where innovation can thrive, pushing the boundaries of what data analysis can achieve.

This desktop application integrates Jupyter Notebook and Python, allowing for a seamless one-click installation. It features engaging code snippets alongside an AI assistant that enhances coding efficiency, making it an ideal tool for data science endeavors. We have meticulously developed over 100 interactive code recipes tailored for your Data Science projects, which can identify available packages within your current environment. With a single click, you can install any required modules, streamlining your workflow significantly. Users can easily create and manipulate all variables present in their Python session, while these interactive recipes expedite the completion of tasks. The AI Assistant, equipped with knowledge of your active Python session, variables, and modules, is designed to address data challenges using the Python programming language. It offers support for various tasks, including plotting, data loading, data wrangling, and machine learning. If you encounter code issues, simply click the Fix button, and the AI assistant will analyze the problem and suggest a viable solution, making your coding experience smoother and more productive. Additionally, this innovative tool not only simplifies coding but also enhances your learning curve in data science.

A platform designed for life scientists focusing on data science. Transform your microbiome investigations into actionable insights and expedite the introduction of innovative, safe, and efficient products to the marketplace. By integrating appropriate data science methodologies and collaborative tools, you can achieve swift progress in cancer treatment advancements. Enhance your research efforts, foster innovation, and create substantial value through the implementation of effective digital technologies that enhance agricultural output. You can easily import both small and large datasets, organizing them using our provided templates or customizing your own structure. Our format inference technology generates parsing functions while allowing you to make adjustments without any coding required. Utilize our user-friendly import interfaces or command-line tools for bulk data uploads. Your information represents more than mere data points; Solvuu automatically provides pertinent summary statistics and produces engaging, interactive visualizations. Dive deep into your data for immediate insights and manipulate it freely as necessary, ensuring a thorough understanding of your research findings. With this platform, you will efficiently harness the power of your data for impactful results.

Decision intelligence aims to empower employees with the ability to make faster, more informed decisions that will allow them to take corrective steps, capitalize on opportunities, and drive innovation. The data and analytics platform that is purpose-built to help enterprises make better, faster decisions. A new type of engine drives it. Streamlining the entire analysis workflow. One platform for all data, any person, and any analytics needs. This is the future for intelligent decisions. This new platform combines data preparation, data science, and business analytics into one integrated platform. Streamline all aspects of decision-making. Everything from discovery to publishing to modeling is interconnected (and easy-to-use). It can be run at hyper-scale to support any data-driven decision. Advanced data science is available for all business needs, from the C-Suite to frontline.

Darwin is an automated machine-learning product that allows your data science and business analysis teams to quickly move from data to meaningful results. Darwin assists organizations in scaling the adoption of data science across their teams and the implementation machine learning applications across operations to become data-driven enterprises.