Alternatives to SAS Visual Data Science Decisioning

Domo puts data to work for everyone so they can multiply their impact on the business. Underpinned by a secure data foundation, our cloud-native data experience platform makes data visible and actionable with user-friendly dashboards and apps. Domo helps companies optimize critical business processes at scale and in record time to spark bold curiosity that powers exponential business results.

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.

JMP is a data analysis tool compatible with both Mac and Windows that merges robust statistical capabilities with engaging interactive visualizations. The software simplifies the process of importing and analyzing data through its user-friendly drag-and-drop interface, interconnected graphs, an extensive library of advanced analytic features, a scripting language, and various sharing options, enabling users to explore their datasets more efficiently and effectively. Initially created in the 1980s to leverage the potential of graphical user interfaces for personal computing, JMP continues to evolve by incorporating innovative statistical techniques and specialized analysis methods from diverse industries with each new version released. Furthermore, John Sall, the founder of the organization, remains actively involved as the Chief Architect, ensuring the software stays at the forefront of analytical technology.

Lucidchart is a comprehensive visual collaboration platform that empowers teams to create intelligent, data-driven diagrams for process mapping, team planning, systems architecture, and more. With features like AI-powered diagram generation, real-time collaboration, and data integration, Lucidchart helps users quickly visualize their systems and workflows with ease. Whether you’re building technical diagrams or mapping out complex organizational structures, Lucidchart streamlines the process, saving you time and improving clarity. It integrates with a variety of popular tools such as Jira, Slack, Confluence, and Notion, making it an invaluable tool for enhancing teamwork, driving decisions, and accelerating innovation across your organization.

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.

ZinkML is an open-source data science platform that does not require any coding. It was designed to help organizations leverage data more effectively. Its visual and intuitive interface eliminates the need for extensive programming expertise, making data sciences accessible to a wider range of users. ZinkML streamlines data science from data ingestion, model building, deployment and monitoring. Users can drag and drop components to create complex pipelines, explore the data visually, or build predictive models, all without writing a line of code. The platform offers automated model selection, feature engineering and hyperparameter optimization, which accelerates the model development process. ZinkML also offers robust collaboration features that allow teams to work seamlessly together on data science projects. By democratizing the data science, we empower businesses to get maximum value out of their data and make better decisions.

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.

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.

RapidMiner is redefining enterprise AI so anyone can positively shape the future. RapidMiner empowers data-loving people from all levels to quickly create and implement AI solutions that drive immediate business impact. Our platform unites data prep, machine-learning, and model operations. This provides a user experience that is both rich in data science and simplified for all others. Customers are guaranteed success with our Center of Excellence methodology, RapidMiner Academy and no matter what level of experience or resources they have.

Access, analyze, and manipulate data to uncover emerging trends and patterns effectively. SAS Visual Data Science provides a unified, self-service platform that enables the creation and sharing of intelligent visualizations alongside interactive reports. Leveraging machine learning, text analytics, and econometric techniques enhances forecasting and optimization capabilities, while also allowing for the management and registration of both SAS and open-source models, whether within projects or as independent entities. Utilize this tool to visualize and identify pertinent relationships within your data. Generate and disseminate interactive reports and dashboards, employing self-service analytics to promptly evaluate potential outcomes for more informed, data-driven decisions. Dive into data exploration and construct or modify predictive analytical models using this solution integrated with SAS® Viya®. By fostering collaboration among data scientists, statisticians, and analysts, teams can iteratively refine models tailored to specific segments or groups, thereby empowering decisions rooted in precise insights. This collaborative approach not only enhances model accuracy but also accelerates the decision-making process significantly.

Enhance the precision of your machine learning models by leveraging publicly accessible datasets. Streamline the process of data discovery and preparation with curated datasets that are not only readily available for machine learning applications but also easily integrable through Azure services. It is essential to consider real-world factors that could influence business performance. By integrating features from these curated datasets into your machine learning models, you can significantly boost the accuracy of your predictions while minimizing the time spent on data preparation. Collaborate and share datasets with an expanding network of data scientists and developers. Utilize Azure Open Datasets alongside Azure’s machine learning and data analytics solutions to generate insights at an unprecedented scale. Most Open Datasets come at no extra cost, allowing you to pay solely for the Azure services utilized, including virtual machine instances, storage, networking, and machine learning resources. This curated open data is designed for seamless access on Azure, empowering users to focus on innovation and analysis. In this way, organizations can unlock new opportunities and drive informed decision-making.

Oracle Analytics is a comprehensive platform designed for all analytics user roles, integrating AI and machine learning across the board to boost productivity and enable smarter business decisions. Whether you opt for Oracle Analytics Cloud, our cloud-native service, or Oracle Analytics Server, our on-premises solution, you can ensure robust security and governance without compromise.

dotData empowers your organization to concentrate on the outcomes of AI and machine learning initiatives, relieving you from the complexities of the data science workflow by automating the entire data science life-cycle. You can launch a complete AI and ML pipeline in just minutes, while benefiting from real-time updates through continuous deployment. This innovation accelerates data science endeavors, reducing timelines from several months to mere days via automated feature engineering. With data science automation, you can uncover the hidden insights within your business effortlessly. The traditional approach to utilizing data science for crafting and implementing precise machine learning and AI models is often laborious, lengthy, and requires collaboration across multiple disciplines. By automating the most tedious and repetitive tasks that plague data science efforts, you can significantly diminish AI development periods, transforming them from months into just days. This shift not only enhances efficiency but also allows teams to redirect their focus toward more strategic initiatives.

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.

Enhance the efficiency of the data mining workflow to expedite model development. Gain insight into critical relationships and identify the most significant patterns. Significantly reduce the time it takes for data miners and statisticians to create models. An intuitive, self-documenting process flow diagram environment effectively outlines the complete data mining procedure to yield optimal outcomes. Furthermore, it boasts a wider array of predictive modeling techniques than any other available commercial data mining software. Why settle for anything less than the best? Business professionals and domain experts with minimal statistical expertise can easily construct their own models using SAS Rapid Predictive Modeler. Its user-friendly interface guides them through a sequence of data mining activities. The analytics findings are presented in straightforward charts that deliver the clarity required for improved decision-making. Leverage cutting-edge algorithms and industry-adapted methods to develop superior models. Additionally, confirm the accuracy of results through visual evaluations and validation metrics, ensuring a robust modeling process. This comprehensive approach not only enhances model performance but also empowers users to make informed choices with confidence.

We specialize in creating, overseeing, and operating predictive software solutions that utilize data science and machine learning technologies. Our services cater to sizable e-commerce companies and retail chains, employing machine learning techniques to accurately predict sales and enhance stock distribution across various retail locations and warehouses. We also offer a personalized product recommendation system for online retailers that leverages real-time Bayesian networks to present visitors with tailored product suggestions. Additionally, our software automatically recommends price adjustments aimed at maximizing profits by applying statistical models of price and demand elasticity. Moreover, we provide an API designed to calculate optimal routing for batch picking processes in a retailer’s warehouse, utilizing advanced shortest path graph algorithms for efficiency improvements. By integrating these innovative tools, we empower businesses to make data-driven decisions that enhance overall operational performance.

Experience the entire journey of developing machine learning algorithms and forecasting results with just a single click. Not every dataset is inherently suitable for machine learning; leverage the Data Dialog to effortlessly refine your data without the hassle of file manipulation. You can easily distribute your prediction reports among your team or make them publicly accessible, allowing anyone to engage with your model and generate predictions. Integrate dynamic ML predictions directly into your application through our user-friendly low-code API. Assess factors like willingness to pay, evaluate leads, and more, all in real-time. Obviously AI equips you with the latest groundbreaking algorithms while ensuring top-notch performance is maintained. You can now accurately forecast revenue, streamline supply chains, and tailor marketing efforts to individual needs. With just a CSV upload or a quick integration with your preferred data sources, you can select your prediction column from a convenient dropdown menu and watch as we automatically construct the AI for you. Additionally, enjoy beautifully crafted visualizations of predicted outcomes, identify key influencers, and explore "what-if" scenarios to better understand potential futures. This innovative approach transforms the way you interact with data and make predictions.

Apache Spark™ serves as a comprehensive analytics platform designed for large-scale data processing. It delivers exceptional performance for both batch and streaming data by employing an advanced Directed Acyclic Graph (DAG) scheduler, a sophisticated query optimizer, and a robust execution engine. With over 80 high-level operators available, Spark simplifies the development of parallel applications. Additionally, it supports interactive use through various shells including Scala, Python, R, and SQL. Spark supports a rich ecosystem of libraries such as SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming, allowing for seamless integration within a single application. It is compatible with various environments, including Hadoop, Apache Mesos, Kubernetes, and standalone setups, as well as cloud deployments. Furthermore, Spark can connect to a multitude of data sources, enabling access to data stored in systems like HDFS, Alluxio, Apache Cassandra, Apache HBase, and Apache Hive, among many others. This versatility makes Spark an invaluable tool for organizations looking to harness the power of large-scale data analytics.

Deepnote is building the best data science notebook for teams. Connect your data, explore and analyze it within the notebook with real-time collaboration and versioning. Share links to your projects with other analysts and data scientists on your team, or present your polished, published notebooks to end users and stakeholders. All of this is done through a powerful, browser-based UI that runs in the cloud.

Empowering businesses to engage in genuine data science quickly and effectively through a comprehensive machine learning platform is crucial. By minimizing the time spent managing tools and infrastructure, organizations can concentrate on developing machine learning applications that drive growth. Anaconda Enterprise alleviates the challenges associated with ML operations, grants access to open-source innovations, and lays the groundwork for robust data science and machine learning operations without confining users to specific models, templates, or workflows. Software developers and data scientists can seamlessly collaborate within AE to create, test, debug, and deploy models using their chosen programming languages and tools. Additionally, AE facilitates access to both notebooks and integrated development environments (IDEs), enhancing collaborative efficiency. Users can also select from a variety of example projects or utilize preconfigured projects tailored to their needs. Furthermore, AE automatically containerizes projects, ensuring they can be effortlessly transitioned between various environments as required. This flexibility ultimately empowers teams to innovate and adapt to changing business demands more readily.

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.

DSVMs, or Data Science Virtual Machines, are pre-configured Azure Virtual Machine images equipped with a variety of widely-used tools for data analysis, machine learning, and AI training. They ensure a uniform setup across teams, encouraging seamless collaboration and sharing of resources while leveraging Azure's scalability and management features. Offering a near-zero setup experience, these VMs provide a fully cloud-based desktop environment tailored for data science applications. They facilitate rapid and low-friction deployment suitable for both classroom settings and online learning environments. Users can execute analytics tasks on diverse Azure hardware configurations, benefiting from both vertical and horizontal scaling options. Moreover, the pricing structure allows individuals to pay only for the resources they utilize, ensuring cost-effectiveness. With readily available GPU clusters that come pre-configured for deep learning tasks, users can hit the ground running. Additionally, the VMs include various examples, templates, and sample notebooks crafted or validated by Microsoft, which aids in the smooth onboarding process for numerous tools and capabilities, including but not limited to Neural Networks through frameworks like PyTorch and TensorFlow, as well as data manipulation using R, Python, Julia, and SQL Server. This comprehensive package not only accelerates the learning curve for newcomers but also enhances productivity for seasoned data scientists.

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.

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.

Dataiku serves as a sophisticated platform for data science and machine learning, aimed at facilitating teams in the construction, deployment, and management of AI and analytics projects on a large scale. It enables a diverse range of users, including data scientists and business analysts, to work together in developing data pipelines, crafting machine learning models, and preparing data through various visual and coding interfaces. Supporting the complete AI lifecycle, Dataiku provides essential tools for data preparation, model training, deployment, and ongoing monitoring of projects. Additionally, the platform incorporates integrations that enhance its capabilities, such as generative AI, thereby allowing organizations to innovate and implement AI solutions across various sectors. This adaptability positions Dataiku as a valuable asset for teams looking to harness the power of AI effectively.

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.

Amazon QuickSight empowers individuals within organizations to gain insights from their data by posing questions in everyday language, navigating through dynamic dashboards, or utilizing machine learning to identify trends and anomalies. It facilitates millions of dashboard interactions each week for notable clients such as the NFL, Expedia, Volvo, Thomson Reuters, Best Western, and Comcast, enabling their users to make informed, data-driven choices. By engaging in conversational inquiries about your data, you can utilize Q's machine learning capabilities to generate pertinent visualizations without the need for extensive data preparation by authors and administrators. This platform also enables the discovery of concealed insights, accurate forecasting, and scenario analysis, while providing the option to enrich dashboards with clear, natural language narratives, all made possible by AWS's machine learning expertise. Additionally, users can seamlessly incorporate interactive visualizations, advanced dashboard design features, and natural language querying capabilities into their applications, streamlining the process of data analysis across various platforms. Thus, QuickSight not only enhances the way organizations interact with their data but also simplifies the journey of transforming raw information into actionable insights.

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.

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.

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.

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.

TADA by MyDataModels offers a top-tier predictive analytics solution that enables professionals to leverage their Small Data for business improvement through a user-friendly and easily deployable tool. With TADA, users can quickly develop predictive models that deliver actionable insights in a fraction of the time, transforming what once took days into mere hours thanks to an automated data preparation process that reduces time by 40%. This platform empowers individuals to extract valuable outcomes from their data without the need for programming expertise or advanced machine learning knowledge. By utilizing intuitive and transparent models composed of straightforward formulas, users can efficiently optimize their time and turn raw data into meaningful insights effortlessly across various platforms. The complexity of predictive model construction is significantly diminished as TADA automates the generative machine learning process, making it as simple as inputting data to receive a model output. Moreover, TADA allows for the creation and execution of machine learning models on a wide range of devices and platforms, ensuring accessibility through its robust web-based pre-processing capabilities, thereby enhancing operational efficiency and decision-making.

Harness the potential of your data through engaging dashboards and stunning reports that facilitate more informed business choices. It's simple and at no cost. You can effortlessly tap into a diverse array of data sources. The connectors available in Data Studio, both built-in and from partners, enable connections to nearly any data type. Transform your data into captivating narratives that showcase the artistry of data visualization. With Data Studio’s online reporting tools, you can swiftly create interactive dashboards and reports. Share these insightful reports and dashboards with colleagues, teams, or a global audience. Collaborate dynamically in real time and even embed your reports on any website for broader accessibility. This seamless integration allows for enhanced communication and understanding within your organization.

IBM Analytics for Apache Spark offers a versatile and cohesive Spark service that enables data scientists to tackle ambitious and complex inquiries while accelerating the achievement of business outcomes. This user-friendly, continually available managed service comes without long-term commitments or risks, allowing for immediate exploration. Enjoy the advantages of Apache Spark without vendor lock-in, supported by IBM's dedication to open-source technologies and extensive enterprise experience. With integrated Notebooks serving as a connector, the process of coding and analytics becomes more efficient, enabling you to focus more on delivering results and fostering innovation. Additionally, this managed Apache Spark service provides straightforward access to powerful machine learning libraries, alleviating the challenges, time investment, and risks traditionally associated with independently managing a Spark cluster. As a result, teams can prioritize their analytical goals and enhance their productivity significantly.

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.

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.

Constantly accessible, real-time business decision-making is achievable without requiring specialized tools or resources. UBIX stands out as an innovator at the crossroads of generative AI and reinforcement learning, facilitating actionable insights and automation driven by business needs. Our unique no-code SaaS platform swiftly contextualizes and displays data from both internal and external sources within minutes, revolutionizing the transformation of AI and machine learning innovations. This approach enhances everyday decision-making that influences productivity, waste management, compliance, growth, and profitability. We ensure the right data reaches the appropriate business leader at the optimal moment and in the best format. By following just five simple steps over a few days, organizations can seamlessly integrate AI capabilities into their operations. This not only strengthens business intelligence efforts but also liberates data scientists to focus on innovation rather than routine reporting tasks. The power of artificial intelligence is no longer confined to large enterprises or technical teams; it is now accessible to individuals in organizations of every size. With UBIX, advanced analytics and artificial intelligence become a resource available to all.

Bitfount serves as a collaborative platform for distributed data science, enabling deep collaborations without the need for data sharing. The innovative approach of distributed data science allows algorithms to be deployed directly to where the data resides, rather than moving the data itself. In just a few minutes, you can establish a federated network for privacy-preserving analytics and machine learning, freeing your team to concentrate on generating insights and fostering innovation rather than getting bogged down by bureaucratic processes. While your data team possesses the expertise needed to tackle significant challenges and drive innovation, they often face obstacles related to data accessibility. Are intricate data pipeline infrastructures disrupting your strategies? Is the compliance process taking an excessive amount of time? Bitfount offers a more effective solution to empower your data specialists. It enables the connection of disparate and multi-cloud datasets while maintaining privacy and honoring commercial confidentiality. Say goodbye to costly and time-consuming data migrations, as our platform provides usage-based access controls that guarantee teams can only conduct analyses on the data you permit. Moreover, the management of these access controls can be seamlessly transferred to the teams that actually manage the data, streamlining your operations and enhancing productivity. Ultimately, Bitfount aims to revolutionize the way organizations leverage their data assets for better outcomes.

Einblick offers a swift and highly collaborative platform for data exploration, prediction generation, and application deployment. Our innovative canvases transform the data science process by simplifying the exploration, cleaning, and manipulation of data through a user-friendly interface. Unlike other platforms, we enable real-time collaboration among your entire team, emphasizing that collective decision-making is essential. Stop spending time on manual model adjustments; our AutoML feature is designed to facilitate the creation of transparent predictions and pinpoint crucial influencing factors effortlessly. Einblick also streamlines common analytics tasks into user-friendly operators, allowing you to minimize repetitive work and reach conclusions more quickly. Whether your data resides in Snowflake, S3 buckets, or CSV files, you can connect your data source and start drawing insights in no time. For instance, by analyzing a list of churned and active customers, you can integrate all relevant information about them, revealing the primary reasons for churn and assessing the risk level for each customer effectively. Moreover, our platform empowers teams to make data-driven decisions with confidence, ensuring that insights are accessible and actionable for everyone involved.

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.

Tatsoft's FactoryStudio provides the tools you need to quickly design secure and powerful industrial applications. Features include real-time data modeling and data logging, MQTT client/spB broker/spB, audit trails, alarms & incidents, visual SQL query gateway, high-performance smart screens, HTML5 dashboards. WPF drawing tools. iOS app, trends, annotations, reporting & much more! Programming scripts can be done in C#, VB.NET or JavaScript. You can get up and running in no time with ZERO client install and just 2 minutes server side installation. It includes many native protocol drivers for PLCs, DCSs, as well as support for other industry standards like OPC, MQTT, and more. Are you looking for a driver that we don't yet have? We also have a toolkit to help you develop protocol drivers! FactoryStudio is your data hub for your industrial ecosystem. It can be your link between IT, OT, real-time devices and your SQL data sources.

NVIDIA Merlin equips data scientists, ML engineers, and researchers with the tools necessary to create scalable, high-performance recommendation systems. This suite includes libraries, methodologies, and various tools that simplify the process of building recommenders by tackling prevalent issues related to preprocessing, feature engineering, training, inference, and production deployment. Optimized components within Merlin facilitate the retrieval, filtering, scoring, and organization of vast data sets, often reaching hundreds of terabytes, all accessed via user-friendly APIs. The implementation of Merlin enables enhanced predictions, improved click-through rates, and quicker production deployment, making it an essential resource for professionals. As a part of NVIDIA AI, Merlin exemplifies the company's dedication to empowering innovative practitioners in their work. Furthermore, this comprehensive solution is crafted to seamlessly integrate with existing recommender systems that leverage both data science and machine learning techniques, ensuring that users can build on their current workflows effectively.

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.

Data plays an essential role in the process of establishing, optimizing, and expanding your enterprise. Nevertheless, fully harnessing the potential of data can prove difficult as many businesses encounter issues like limited data access, mismatched tools, escalating expenses, and delayed outcomes. In simple terms, those who can effectively convert unrefined data into actionable insights will excel in the current business environment. A crucial aspect of achieving this is enabling all team members to analyze, create, and collaborate on comprehensive AI and machine learning projects efficiently and within a unified platform. Streamflux serves as a comprehensive solution for addressing your data analytics and AI needs. Our user-friendly platform empowers you to construct complete data solutions, utilize models to tackle intricate inquiries, and evaluate user interactions. Whether your focus is on forecasting customer attrition, estimating future earnings, or crafting personalized recommendations, you can transform raw data into meaningful business results within days rather than months. By leveraging our platform, organizations can not only enhance efficiency but also foster a culture of data-driven decision-making.

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.