Alternatives to KNIME Analytics Platform

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.

Tableau, a comprehensive business intelligence (BI/analytics) solution, allows you to generate, analyze, and interpret business data. Tableau allows users to gather data from many sources, including spreadsheets, SQL databases and Salesforce. Tableau offers real-time visual analytics as well as an interactive dashboard that allows users to slice and dice data to make relevant insights and find new opportunities. Tableau allows users to customize the platform for different industry verticals such as communication, banking, and more.

TIMi allows companies to use their corporate data to generate new ideas and make crucial business decisions more quickly and easily than ever before. The heart of TIMi’s Integrated Platform. TIMi's ultimate real time AUTO-ML engine. 3D VR segmentation, visualization. Unlimited self service business Intelligence. TIMi is a faster solution than any other to perform the 2 most critical analytical tasks: data cleaning, feature engineering, creation KPIs, and predictive modeling. TIMi is an ethical solution. There is no lock-in, just excellence. We guarantee you work in complete serenity, without unexpected costs. TIMi's unique software infrastructure allows for maximum flexibility during the exploration phase, and high reliability during the production phase. TIMi allows your analysts to test even the most crazy ideas.

Composable is an enterprise-grade DataOps platform designed for business users who want to build data-driven products and create data intelligence solutions. It can be used to design data-driven products that leverage disparate data sources, live streams, and event data, regardless of their format or structure. Composable offers a user-friendly, intuitive dataflow visual editor, built-in services that facilitate data engineering, as well as a composable architecture which allows abstraction and integration of any analytical or software approach. It is the best integrated development environment for discovering, managing, transforming, and analysing enterprise data.

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

Data analysts, engineers, scientists, and other scientists can be brought together. Automate self-service analytics and machine learning operations. Get results today, build for tomorrow. Dataiku DSS is a collaborative data science platform that allows data scientists, engineers, and data analysts to create, prototype, build, then deliver their data products more efficiently. Use notebooks (Python, R, Spark, Scala, Hive, etc.) You can also use a drag-and-drop visual interface or Python, R, Spark, Scala, Hive notebooks at every step of the predictive dataflow prototyping procedure - from wrangling to analysis and modeling. Visually profile the data at each stage of the analysis. Interactively explore your data and chart it using 25+ built in charts. Use 80+ built-in functions to prepare, enrich, blend, clean, and clean your data. Make use of Machine Learning technologies such as Scikit-Learn (MLlib), TensorFlow and Keras. In a visual UI. You can build and optimize models in Python or R, and integrate any external library of ML through code APIs.

Alteryx AI Platform will help you enter a new age of analytics. Empower your organization through automated data preparation, AI powered analytics, and accessible machine learning - all with embedded governance. Welcome to a future of data-driven decision making for every user, team and step. Empower your team with an intuitive, easy-to-use user experience that allows everyone to create analytical solutions that improve productivity and efficiency. Create an analytics culture using an end-toend cloud analytics platform. Data can be transformed into insights through self-service data preparation, machine learning and AI generated insights. Security standards and certifications are the best way to reduce risk and ensure that your data is protected. Open API standards allow you to connect with your data and applications.

Model building software for today's machine learning age incorporates credit risk modelling expertise spanning over thirty years. Modeller is a flexible, transparent, interactive, and feature-rich tool that helps organizations get more out of their analytical teams. It allows for a variety of techniques, rapid development of powerful models, full explanation, and advancement of less experienced members of the team. You can choose from a variety of modeling techniques, including machine-learning, to achieve optimal predictive accuracy, especially when working with complex interrelationships and multicollinearity. At the touch of a button, you can create industry-standard binary and continuous target models. You can use decision tree modeling with CHAID trees and CART. You can choose from logistic regression, elastic network models, survival analysis (Cox PH), random forest, XGBoost and stochastic gradient descend. SAS, SQL and PMML are all available export options for use in other scoring and decisioning programs.

H2O.ai, the open-source leader in AI and machinelearning, has a mission to democratize AI. Our enterprise-ready platforms, which are industry-leading, are used by thousands of data scientists from over 20,000 organizations worldwide. Every company can become an AI company in financial, insurance, healthcare and retail. We also empower them to deliver real value and transform businesses.

Predictive modeling with Machine Learning and Explainable Ai. FICO®, Analytics Workbench™, is a comprehensive suite of state-of the-art analytic authoring software that empowers companies to make better business decisions throughout the customer lifecycle. Data scientists can use it to build superior decisioning abilities using a variety of predictive data modeling tools, including the most recent machine learning (ML), and explainable AI (xAI) methods. FICO's innovative intellectual property enables us to combine the best of open-source data science and machine learning to provide world-class analytical capabilities to find, combine, and operationalize data predictive signals. Analytics Workbench is built upon the FICO®, leading platform that allows for new predictive models and strategies to easily be put into production.

Neural Designer is a data-science and machine learning platform that allows you to build, train, deploy, and maintain neural network models. This tool was created to allow innovative companies and research centres to focus on their applications, not on programming algorithms or programming techniques. Neural Designer does not require you to code or create block diagrams. Instead, the interface guides users through a series of clearly defined steps. Machine Learning can be applied in different industries. These are some examples of machine learning solutions: - In engineering: Performance optimization, quality improvement and fault detection - In banking, insurance: churn prevention and customer targeting. - In healthcare: medical diagnosis, prognosis and activity recognition, microarray analysis and drug design. Neural Designer's strength is its ability to intuitively build predictive models and perform complex operations.

Combine Data Science, Business Intelligence and Data Management Capabilities into One Integrated, Self-Serve Platform. Analance is an end-to-end platform with robust and salable features that combines Data Science and Advanced Analytics, Business Intelligence and Data Management into a single integrated platform. It provides core analytical processing power to ensure that data insights are easily accessible to all, performance remains consistent over time, and business objectives can be met within a single platform. Analance focuses on making quality data into accurate predictions. It provides both citizen data scientists and data scientists with pre-built algorithms as well as an environment for custom programming. Company - Overview Ducen IT provides advanced analytics, business intelligence, and data management to Fortune 1000 companies through its unique data science platform Analance.

You can build, run, and manage AI models and optimize decisions across any cloud. IBM Watson Studio allows you to deploy AI anywhere with IBM Cloud Pak®, the IBM data and AI platform. Open, flexible, multicloud architecture allows you to unite teams, simplify the AI lifecycle management, and accelerate time-to-value. ModelOps pipelines automate the AI lifecycle. AutoAI accelerates data science development. AutoAI allows you to create and programmatically build models. One-click integration allows you to deploy and run models. Promoting AI governance through fair and explicable AI. Optimizing decisions can improve business results. Open source frameworks such as PyTorch and TensorFlow can be used, as well as scikit-learn. You can combine the development tools, including popular IDEs and Jupyter notebooks. JupterLab and CLIs. This includes languages like Python, R, and Scala. IBM Watson Studio automates the management of the AI lifecycle to help you build and scale AI with trust.

Machine Learning and Predictive Analytics Platform. Advanced artificial intelligence is a pre-built platform for machine learning and big-data analytics that can enhance data-driven decision making. OpenText Magellan makes predictive analytics easy to use and provides flexible data visualizations that maximize business intelligence. Artificial intelligence software reduces the need to manually process large amounts of data. It presents valuable business insights in a manner that is easily accessible and relevant to the organization's most important objectives. Organizations can enhance business processes by using a curated combination of capabilities such as predictive modeling, data discovery tools and data mining techniques. IoT data analytics is another way to use data to improve decision-making based on real business intelligence.

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

Unutilized data is the biggest obstacle to scaling AI-powered decision making. IBM Cloud Pak®, for Data is a unified platform that provides a data fabric to connect, access and move siloed data across multiple clouds or on premises. Automate policy enforcement and discovery to simplify access to data. A modern cloud data warehouse integrates to accelerate insights. All data can be protected with privacy and usage policy enforcement. To gain faster insights, use a modern, high-performance cloud storage data warehouse. Data scientists, analysts, and developers can use a single platform to create, deploy, and manage trusted AI models in any cloud.

To quickly develop models, streamline the data mining process. Learn the key relationships. Find the most important patterns. Your data miners and statisticians will be able to significantly reduce the time it takes to create models. A self-documenting interactive process flow diagram environment maps the entire data mining process for the best results. It also has more predictive modeling techniques that any commercial data mining program. Why not choose the best? SAS Rapid Predictive Modeller is available for business users and subject-matter specialists with limited statistical skills. A simple-to-use GUI guides them through the data mining process. Analytics results are presented in simple-to-understand charts that provide insights necessary for better decision-making. Use industry-specific methods and innovative algorithms to create models that are more efficient. Visual assessment and validation metrics are used to verify results.

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.

A fully-featured machine learning platform empowers enterprises to conduct real data science at scale and speed. You can spend less time managing infrastructure and tools so that you can concentrate on building machine learning applications to propel your business forward. Anaconda Enterprise removes the hassle from ML operations and puts open-source innovation at the fingertips. It provides the foundation for serious machine learning and data science production without locking you into any specific models, templates, workflows, or models. AE allows data scientists and software developers to work together to create, test, debug and deploy models using their preferred languages. AE gives developers and data scientists access to both notebooks as well as IDEs, allowing them to work more efficiently together. They can also choose between preconfigured projects and example projects. AE projects can be easily moved from one environment to the next by being automatically packaged.

With open-source Metaflow, you can design and develop data-intensive projects. You can scale them up and deploy them on the fully managed Outerbounds platform. All your data science and ML projects can be managed from one platform. Access data securely from existing data warehouses. A cluster that is optimized for cost and scale can be used to compute. 24/7 managed orchestration of production workflows. Results can be used to power any application. Your engineers will give your data scientists superpowers. Outerbounds Platform enables data scientists to quickly develop, experiment at scale, then deploy to production with confidence. All within the boundaries of your engineers' policies and processes, all running on your cloud account, fully supported by us. Security is part of our DNA, not at its perimeter. Through multiple layers of security, the platform adapts to your policies. Centralized authentication, a strict permission limit, and granular task execution role.

Snowflake®, a cloud data platform and enterprise-grade architecture, allows you to securely store and use your data in the cloud. Drag-and-drop visual workflow design and built-in ETL to connect, clean and transform data from 250+ sources. You can generate actionable insights and insights from your data using the latest Search and AI-driven technology. Our AI/ML environments can be used to build, tune, and deploy models for predictive analytics or forecasting. Our AI/ML environments are available to help you take your data to new heights. The PurpleCube Data Science module allows you to create, train, tune, and deploy AI models for forecasting and predictive analysis. PurpleCube Analytics allows you to create BI visualizations, search your data with natural language and use AI-driven insights and smart recommendations to provide answers to questions that you didn't know to ask.

IBM Analytics for Apache Spark allows data scientists to ask more difficult questions and deliver business value quicker with a flexible, integrated Spark service. It's a simple-to-use, managed service that is always on and doesn't require any long-term commitment. You can start exploring immediately. You can access the power of Apache Spark without locking yourself in, thanks to IBM's open-source commitment as well as decades of enterprise experience. With Notebooks as a connector, coding and analytics are faster and easier with managed Spark services. This allows you to spend more time on innovation and delivery. You can access the power of machine learning libraries through managed Apache Spark services without having to manage a Sparkcluster by yourself.

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.

Metacoder makes data processing faster and more efficient. Metacoder provides data analysts with the flexibility and tools they need to make data analysis easier. Metacoder automates data preparation steps like cleaning, reducing the time it takes to inspect your data before you can get up and running. It is a good company when compared to other companies. Metacoder is cheaper than similar companies and our management is actively developing based upon our valued customers' feedback. Metacoder is primarily used to support predictive analytics professionals in their work. We offer interfaces for database integrations, data cleaning, preprocessing, modeling, and display/interpretation of results. We make it easy to manage the machine learning pipeline and help organizations share their work. Soon, we will offer code-free solutions for image, audio and video as well as biomedical data.

Stata is a comprehensive, integrated software package that can handle all aspects of data science: data manipulation, visualization and statistics, as well as automated reporting. 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.

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.

Machine learning uncovers hidden patterns in enterprise data and generates new value for businesses. Oracle Machine Learning makes it easier to create and deploy machine learning models for data scientists by using AutoML technology and reducing data movement. It also simplifies deployment. Apache Zeppelin notebook technology, which is open-source-based, can increase developer productivity and decrease their learning curve. Notebooks are compatible with SQL, PL/SQL and Python. Users can also use markdown interpreters for Oracle Autonomous Database to create models in their preferred language. No-code user interface that supports AutoML on Autonomous Database. This will increase data scientist productivity as well as non-expert users' access to powerful in-database algorithms to classify and regression. Data scientists can deploy integrated models using the Oracle Machine Learning AutoML User Interface.

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

Access, explore, and prepare data while discovering new patterns and trends. SAS Visual Data Science allows you to create and share interactive visualizations and reports using a single interface. It uses machine learning, text analysis, and econometrics to improve forecasting and optimization. Additionally, it registers SAS and open source models within projects and as standalone models. Visualize your data and find relevant relationships. You can create and share interactive dashboards and reports, and use self service analytics to quickly assess possible outcomes for better, data-driven decisions. This solution runs in SAS®, Viya®. It allows you to explore data and create or adjust predictive analytical models. Analysts, statisticians, data scientists, and analysts can work together to refine and refine models for each group or segment, allowing them to make informed decisions.

Bitfount provides a platform for distributed data sciences. We enable deep data collaborations that do not require data sharing. Distributed data science connects algorithms to data and not the other way around. In minutes, you can set up a federated privacy protecting analytics and machine learning network. This will allow your team to focus on innovation and insights instead of bureaucracy. Although your data team is equipped with the skills to solve your most difficult problems and innovating, they are hindered by data access barriers. Are you having trouble accessing your data? Are compliance processes taking too much time? Bitfount offers a better way for data experts to be unleashed. Connect siloed or multi-cloud data sources while protecting privacy and commercial sensitivity. No expensive, time-consuming data lift-and-shift. Useage-based access control to ensure that teams only do the analysis you need, with the data you want. Transfer access control management to the teams that have the data.

A new decision intelligence system that puts AI in the hands commercial leaders to drive great decisions. Peak has designed CODI, our Connected Intelligence system to be a layer of intelligence between your systems. This allows you to unleash the power of your data, allowing you to make better decisions. CODI allows you to deploy AI solutions quickly and harness the full potential of your data with its unique full-stack capabilities. It gives data science and engineering teams full control over every aspect of building and deploying AI systems, quickly and efficiently. CODI allows AI projects to move beyond being experiments and become fully-deployed solutions with real world value and results. CODI, which is built on enterprise-grade infrastructure allows for data to be handled at scale and seamlessly integrates with existing tech stacks. Combine data from different departments to get more insight.

NVIDIA Merlin enables data scientists, machine-learning engineers, and researchers, to build high-performance recommenders at scale. Merlin includes libraries, methods and tools to streamline the building and deployment of recommenders. These include addressing common challenges in preprocessing, feature engineering and training. Merlin components and capabilities have been optimized to support retrieval, scoring, filtering and ordering of hundreds terabytes data. All of this is accessible via easy-to-use interfaces. Merlin can help you make better predictions, increase click-through rates and deploy faster to production. NVIDIA Merlin is part of NVIDIA AI and advances our commitment to support innovative practitioners doing their best. NVIDIA Merlin is designed as an end-toend solution that can be integrated into existing recommender workflows utilizing data science and machine learning.

HyperCube is the platform that data scientists use to quickly discover hidden insights, no matter what your business needs. Use your business data to make an impact. Unlock understanding, uncover untapped opportunities, make predictions, and avoid risk before they happen. HyperCube turns huge amounts of data into actionable insights. HyperCube is for you, whether you are a beginner or an expert in machine learning. It is the data science Swiss Army knife. It combines proprietary and open-source code to deliver a wide variety of data analysis features right out of the box. Or, it can be customized for your business. We are constantly improving our technology to deliver the best possible results. Choose from apps, DaaS (data-as-a service) or vertical market solutions.

BDB is a modern data analysis and BI platform that can dig deep into your data to uncover actionable insights. It can be deployed on-premise or in the cloud. Our unique microservices-based architecture includes elements such as Data Preparation and Predictive, Pipeline, Dashboard designer, and Pipeline. This allows us to offer customized solutions and scalable analysis to different industries. BDB's NLP-based search allows users to access the data power on desktop, tablet, and mobile. BDB is equipped with many data connectors that allow it to connect to a variety of data sources, apps, third-party API's, IoT and social media. It works in real-time. It allows you to connect to RDBMS and Big data, FTP/ SFTP Server flat files, web services, and FTP/ SFTP Server. You can manage unstructured, semi-structured, and structured data. Get started on your journey to advanced analysis today.

Einblick is the fastest and most collaborative method to analyze data, make predictions, and then deploy data apps. Our canvases dramatically change the data science workflows. They make it easier to clean, manipulate, and explore data in a new interface. Our platform is the only one that allows you to collaborate with your entire team in real-time. Let's make decision-making a team activity. Don't waste your time tuning models manually. AutoML's goal is to help you make clear predictions and identify key drivers quickly. Einblick combines common analytics functionality into simple-to-use operators that allow you to abstract repetitive tasks and get answers faster. Connect your data source to Snowflake, S3 buckets, or CSV files and you'll be able to get answers in minutes. You can create a list of customers that have been churned or are currently churned, and share everything you know about them. Find out the key factors that caused churn and how at-risk each customer is.

Kuzzle IoT Platform: Activate online without any commitment. Kuzzle is an open-source software company that publishes software for managing data, APIs, and the Internet of Things. Kuzzle solutions, developed by French engineers and conceived by them, accelerate the deployment of applications by using an open-source standard. Our teams are available to support you with your IoT project. Connect and manage your area while offering smart services to your users. Kuzzle IoT can help you create an urban hyper vision to manage public lighting, waste, voluntary drop-offs, water, public buildings and parking. Kuzzle IoT works with all IoT devices and sensor technologies. We offer ready-to-use IoT functionality for all your needs, including asset tracking, geolocation, and geofencing. Simplify your IoT application deployment. Online, you can activate the power of Kuzzle IoT without any commitment.

Appsilon offers innovative data analytics, machine-learning, and managed services for Fortune 500 companies, NGOs and non-profit organizations. We offer the most advanced R Shiny applications in the world, and have the unique ability to quickly develop and scale enterprise Shiny dashboards. Our machine learning frameworks enable us to deliver prototypes for Computer Vision, NLP and fraud detection in as little as one working week. We are determined to make a positive difference in the world. Our AI For Good Initiative allows us to contribute our expertise to projects that help preserve human life and conserve animal populations around the world. Our team has been working to reduce poaching in Africa using computer vision, provide satellite imagery analysis to assess damage after natural catastrophes, and develop tools to aid with COVID-19 risk assessments. Appsilon is also an innovator in open-source.

An end-to-end solution gives you all the tools your data science team needs to scale your machine learning development, from research to production. cnvrg.io, the world's leading data science platform for MLOps (model management) is a leader in creating cutting-edge machine-learning development solutions that allow you to build high-impact models in half the time. In a collaborative and clear machine learning management environment, bridge science and engineering teams. Use interactive workspaces, dashboards and model repositories to communicate and reproduce results. You should be less concerned about technical complexity and more focused on creating high-impact ML models. The Cnvrg.io container based infrastructure simplifies engineering heavy tasks such as tracking, monitoring and configuration, compute resource management, server infrastructure, feature extraction, model deployment, and serving infrastructure.

Machine learning can be accelerated from research to production using a consistent experience that is built for your traditional platform. Cloudera Data Science Workbench, (CDSW), offers a self-service experience that data scientists will love. It allows you to access Python, R, Scala, and more directly from your web browser. You can download and test the latest frameworks and libraries in project environments that look exactly like your laptop. Cloudera Data Science Workbench allows you to connect to CDH and HDP as well as to the systems that your data science teams depend on for analysis. Cloudera Data Science Workbench allows data scientists to manage their own analytics pipelines. It includes built-in monitoring, scheduling, email alerting, and monitoring. Rapidly create and prototype machine learning projects, and then easily deploy them to production.

Analytically driven decision flows can be created, embedded and managed at scale in batch or real-time. SAS Data Science Programming allows data scientists who prefer to work only in programmatic mode to access SAS analytical capabilities at every stage of the analytics lifecycle, including data discovery and deployment. Visualize and discover relationships in your data. You can create and share interactive dashboards and reports, and use self service analytics to quickly assess possible outcomes to make data-driven, smarter decisions. This solution runs in SAS®, Viya®. It allows you to explore data and create or adjust predictive analytical models. Analysts, statisticians, data scientists, and analysts can work together to refine and refine models for each group or segment, allowing them to make informed decisions. A comprehensive visual interface allows you to solve complex analytical problems. It handles all aspects of the analytics lifecycle.

Data science platform that increases productivity and has unparalleled capabilities. Create and evaluate machine learning (ML), models of higher quality. Easy deployment of ML models can help increase business flexibility and enable enterprise-trusted data work faster. Cloud-based platforms can be used to uncover new business insights. Iterative processes are necessary to build a machine-learning model. This ebook will explain how machine learning models are constructed and break down the process. Use notebooks to build and test machine learning algorithms. AutoML will show you the results of data science. It is easier and faster to create high-quality models. Automated machine-learning capabilities quickly analyze the data and recommend the best data features and algorithms. Automated machine learning also tunes the model and explains its results.

Cloud-based Data Science Platform that delivers intelligently curated, cleansed and ready to consume data. Before they can begin to add value, firms face significant challenges and resource constraints. Data is ingested and then cleaned, stored, accessed and only then analyzed. The value comes from the analysis. Our solution allows our clients to focus on their core business activities and not on the expensive and resource-intensive data lifecycle. We'll take care of it. Cloud-native platform that enables real-time streaming analytics. INQDATA can deliver historical and real-time information without the need for complex infrastructure.

Easily extract, transform, manage & process CAD data, FE data, CFD and test results. Create automatic data pipelines to support machine learning, deep learning, and ROM. Data science barriers can be removed without coding. Key Ward's platform, the first engineering no-code end-to-end solution, redefines how engineers work with their data. Our software allows engineers to handle multi-source data with ease, extract direct value using our built-in advanced analytical tools, and build custom machine and deep learning model with just a few clicks. Automatically centralize, update and extract your multi-source data, then sort, clean and prepare it for analysis, machine and/or deep learning. Use our advanced analytics tools to correlate, identify patterns, and find dependencies in your experimental & simulator data.

SAS®, Viya®, data science offerings offer a comprehensive, scalable analytical environment that is quick and easy to use, allowing you to meet diverse business requirements. Automatically generated insights allow you to identify the most commonly used variables across all models, the most significant variables selected across models, and assess results for all models. Natural language generation capabilities allow you to create project summaries in plain language. This makes it easy to interpret reports. Analytics team members can add project notes and comments to the insights report to facilitate communication between team members. SAS allows you to embed open source code into an analysis and call open-source algorithms seamlessly within its environment. This allows for collaboration within your organization as users can program in the language they prefer. SAS Deep Learning with Python (DLPy) is also available on GitHub.

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.

Accelerate and simplify IoT data extraction, create AI for the shop floor, and visualize KPIs. Manage decentralized, compact data pods. Each data pod is completely autonomous and includes infrastructure for powerful analytics. Flexible storage capacity allows you to create multiple pods with different sizes. In a seamless data journey, you can collect, analyze, visualize, and visualize data. You can collect raw data from multiple sources, such as IoT routers or the web. Instantly generate reports and create custom infographics from your browser. Combine the power of VS Code, Observable and TablePlus to create interactive data science workbooks. You can see the current and past processes in real time and automate package loads up to reporting.

MATLAB®, a combination of a desktop environment for iterative analysis, design processes, and a programming language that expresses matrix or array mathematics directly, is MATLAB®. It also includes the Live Editor, which allows you to create scripts that combine output, code, and formatted text in an executable notebook. MATLAB toolboxes have been professionally developed, tested and documented. MATLAB apps allow you to see how different algorithms interact with your data. You can repeat the process until you get the results you desire. Then, MATLAB will automatically generate a program to replicate or automate your work. With minor code changes, you can scale your analyses to run on GPUs, clusters, and clouds. You don't need to rewrite any code or learn big-data programming and other out-of-memory methods. Convert MATLAB algorithms automatically to C/C++ and HDL to run on your embedded processor/FPGA/ASIC. Simulink works with MATLAB to support Model-Based Design.

Secure and manage the data lifecycle, from Edge to AI in any cloud or data centre. Operates on all major public clouds as well as the private cloud with a public experience everywhere. Integrates data management and analytics experiences across the entire data lifecycle. All environments are covered by security, compliance, migration, metadata management. Open source, extensible, and open to multiple data stores. Self-service analytics that is faster, safer, and easier to use. Self-service access to multi-function, integrated analytics on centrally managed business data. This allows for consistent experiences anywhere, whether it is in the cloud or hybrid. You can enjoy consistent data security, governance and lineage as well as deploying the cloud analytics services that business users need. This eliminates the need for shadow IT solutions.

To identify the best actions, you need to build and solve complex optimization models. IBM®, ILOG®, CPLEX®, Optimization Studio uses decision optimization technology. It optimizes your business decisions, creates and deploys optimization models quickly, and creates real-world applications that can significantly increase business outcomes. How does it work? How? It combines a fully-featured integrated development environment that supports Optimization Programming Language, (OPL), and the high-performance CPLEX/CP Optimizer solvers. It's data science for your decisions. IBM Decision Optimization is also available in Cloud Pak for Data. This allows you to combine optimization and machine-learning within a unified environment, IBM Watson® Studio that enables AI infused optimization modeling capabilities.

Doolytic is a leader in big data discovery, the convergence data discovery, advanced analytics and big data. Doolytic is bringing together BI experts to revolutionize self-service exploration of large data. This will unleash the data scientist in everyone. doolytic is an enterprise solution for native big data discovery. doolytic is built on open-source, scalable technologies that are best-of-breed. Lightening performance on billions and petabytes. Structured, unstructured, and real-time data from all sources. Advanced query capabilities for experts, Integration with R to enable advanced and predictive applications. With Elastic's flexibility, you can search, analyze, and visualize data in real-time from any format or source. You can harness the power of Hadoop data lakes without any latency or concurrency issues. doolytic solves common BI issues and enables big data discovery without clumsy or inefficient workarounds.