Alternatives to IBM Cloud Pak for Data

Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case. Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection.

ANSI SQL allows you to analyze petabytes worth of data at lightning-fast speeds with no operational overhead. Analytics at scale with 26%-34% less three-year TCO than cloud-based data warehouse alternatives. You can unleash your insights with a trusted platform that is more secure and scales with you. Multi-cloud analytics solutions that allow you to gain insights from all types of data. You can query streaming data in real-time and get the most current information about all your business processes. Machine learning is built-in and allows you to predict business outcomes quickly without having to move data. With just a few clicks, you can securely access and share the analytical insights within your organization. Easy creation of stunning dashboards and reports using popular business intelligence tools right out of the box. BigQuery's strong security, governance, and reliability controls ensure high availability and a 99.9% uptime SLA. Encrypt your data by default and with customer-managed encryption keys

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.

Manta is a unified data lineage platform that serves as the central hub of all enterprise data flows. Manta can construct lineage from report definitions, custom SQL code, and ETL workflows. Lineage is analyzed based on actual code, and both direct and indirect flows can be visualized on the map. Data paths between files, report fields, database tables, and individual columns are displayed to users in an intuitive user interface, enabling teams to understand data flows in context.

Illuminate dark data and accelerate data-driven transformation with intelligent data operations to enable an edge-to-cloud data fabric. Pentaho products automate onboarding, integrating, governing, and publishing trusted data, with an intelligent composable data platform to automate data management needs.

AtScale accelerates and simplifies business intelligence. This results in better business decisions and a faster time to insight. Reduce repetitive data engineering tasks such as maintaining, curating, and delivering data for analysis. To ensure consistent KPI reporting across BI tools, you can define business definitions in one place. You can speed up the time it takes to gain insight from data and also manage cloud compute costs efficiently. No matter where your data is located, you can leverage existing data security policies to perform data analytics. AtScale's Insights models and workbooks allow you to perform Cloud OLAP multidimensional analysis using data sets from multiple providers - without any data prep or engineering. To help you quickly gain insights that you can use to make business decisions, we provide easy-to-use dimensions and measures.

Amazon SageMaker, a fully managed service, provides data scientists and developers with the ability to quickly build, train, deploy, and deploy machine-learning (ML) models. SageMaker takes the hard work out of each step in the machine learning process, making it easier to create high-quality models. Traditional ML development can be complex, costly, and iterative. This is made worse by the lack of integrated tools to support the entire machine learning workflow. It is tedious and error-prone to combine tools and workflows. SageMaker solves the problem by combining all components needed for machine learning into a single toolset. This allows models to be produced faster and with less effort. Amazon SageMaker Studio is a web-based visual interface that allows you to perform all ML development tasks. SageMaker Studio allows you to have complete control over each step and gives you visibility.

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.

We make BI and Big Data analytics easier and more efficient. Our goal is to empower business users, make BI specialists and always-busy business more independent when solving data-driven business problems. Querona is a solution for those who have ever been frustrated by a lack in data, slow or tedious report generation, or a long queue to their BI specialist. Querona has a built-in Big Data engine that can handle increasing data volumes. Repeatable queries can be stored and calculated in advance. Querona automatically suggests improvements to queries, making optimization easier. Querona empowers data scientists and business analysts by giving them self-service. They can quickly create and prototype data models, add data sources, optimize queries, and dig into raw data. It is possible to use less IT. Users can now access live data regardless of where it is stored. Querona can cache data if databases are too busy to query live.

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.

data.world is a fully managed cloud service that was built for modern data architectures. We handle all updates, migrations, maintenance. It is easy to set up with our large and growing network of pre-built integrations, including all the major cloud data warehouses. Your team must solve real business problems and not struggle with complicated data software when time-to value is important. data.world makes it simple for everyone, not just the "data people", to get clear, precise, and fast answers to any business question. Our cloud-native data catalog maps siloed, distributed data to consistent business concepts, creating an unified body of knowledge that anyone can understand, use, and find. Data.world is the home of the largest open data community in the world. It is where people come together to work on everything, from data journalism to social bot detection.

K2View believes that every enterprise should be able to leverage its data to become as disruptive and agile as possible. We enable this through our Data Product Platform, which creates and manages a trusted dataset for every business entity – on demand, in real time. The dataset is always in sync with its sources, adapts to changes on the fly, and is instantly accessible to any authorized data consumer. We fuel operational use cases, including customer 360, data masking, test data management, data migration, and legacy application modernization – to deliver business outcomes at half the time and cost of other alternatives.

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.

Manage, control, secure, and manage the apps, data, and IT that run your business from edge to cloud. HPE Ezmeral accelerates digital transformation initiatives by shifting resources and time from IT operations to innovation. Modernize your apps. Simplify your operations. You can harness data to transform insights into impact. Kubernetes can be deployed at scale in your data center or on the edge. It integrates persistent data storage to allow app modernization on baremetal or VMs. This will accelerate time-to-value. Operationalizing the entire process to build data pipelines will allow you to harness data faster and gain insights. DevOps agility is key to machine learning's lifecycle. This will enable you to deliver a unified data network. Automation and advanced artificial intelligence can increase efficiency and agility in IT Ops. Provide security and control to reduce risk and lower costs. The HPE Ezmeral Container Platform is an enterprise-grade platform that deploys Kubernetes at large scale for a wide variety of uses.

Talend Data Fabric's cloud services are able to efficiently solve all your integration and integrity problems -- on-premises or in cloud, from any source, at any endpoint. Trusted data delivered at the right time for every user. With an intuitive interface and minimal coding, you can easily and quickly integrate data, files, applications, events, and APIs from any source to any location. Integrate quality into data management to ensure compliance with all regulations. This is possible through a collaborative, pervasive, and cohesive approach towards data governance. High quality, reliable data is essential to make informed decisions. It must be derived from real-time and batch processing, and enhanced with market-leading data enrichment and cleaning tools. Make your data more valuable by making it accessible internally and externally. Building APIs is easy with the extensive self-service capabilities. This will improve customer engagement.

Platform for developing use-case specific solutions powered by cloud native AI powered Decision Automation platform. Incedo LighthouseTM harnesses AI's power in a low-code environment to deliver action recommendations and insights every day by leveraging the superfast Big Data capabilities. Incedo LighthouseTM allows you to increase your revenue potential by optimizing customer experiences, and delivering hyper-personalized recommendation. Our AI- and ML-driven models allow personalization throughout the customer lifecycle. Incedo LighthouseTM can help you reduce costs by speeding the process of problem discovery, insight generation, and execution of targeted actions. Our ML-driven metric monitoring and root cause analysis models power the platform. Incedo LighthouseTM monitors data quality and uses AI/ML to resolve some quality issues. This improves trust in data.

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.

Arundo Enterprise is a flexible, modular software suite that creates data products for people. We connect live data with machine learning and other analytic models, and model outputs are used to make business decisions. Arundo Edge Agent allows industrial connectivity and analytics in remote, rugged, and disconnected environments. Arundo Composer allows data analysts to quickly and easily deploy desktop-based models into the Arundo Fabric Cloud environment using a single command. Composer allows companies to create and manage data streams and integrate them with their deployed data models. Arundo Fabric, a cloud-based hub that deploys machine learning models, data streams and edge agent management, is Arundo Fabric. It also allows for quick navigation to extended applications. Arundo offers a range of high ROI SaaS products. Each solution comes with a core functional capability that leverages Arundo Enterprise's core strengths.

There are many products that can help companies do this. But if your priorities include creating a data-driven company and being as efficient as possible, Fraxses is the best distributed data platform. Fraxses gives customers access to data on-demand and delivers powerful insights through a data mesh (or data fabric architecture) solution. A data mesh is a structure that can be placed over diverse data sources, connecting them and enabling them all to work together in a single environment. The Fraxses data platform is decentralized, unlike other data integration and virtualization platforms. Although Fraxses supports traditional data integration processes, the future lies with a new approach where data is delivered directly to users without the need of a centrally managed data lake or platform.

Alteryx is the launchpad to automation breakthroughs. The results are unrivalled, whether you're looking for personal growth, rapid innovation, or transformative digital outcomes. This unique innovation combines analytics, data science, and process automation into a single platform that empowers every person and organization to make business-changing breakthroughs.

All your data, analytics, and AI in one unified platform. Databricks is powered by Delta Lake. It combines the best data warehouses with data lakes to create a lakehouse architecture that allows you to collaborate on all your data, analytics, and AI workloads. We are the original developers of Apache Spark™, Delta Lake, and MLflow. We believe open source software is the key to the future of data and AI. Your business can be built on an open, cloud-agnostic platform. Databricks supports customers all over the world on AWS, Microsoft Azure, or Alibaba cloud. Our platform integrates tightly with the cloud providers' security, compute storage, analytics and AI services to help you unify your data and AI workloads.

Delphix is the industry leader for DataOps. It provides an intelligent data platform that accelerates digital change for leading companies around world. The Delphix DataOps Platform supports many systems, including mainframes, Oracle databases, ERP apps, and Kubernetes container. Delphix supports a wide range of data operations that enable modern CI/CD workflows. It also automates data compliance with privacy regulations such as GDPR, CCPA and the New York Privacy Act. Delphix also helps companies to sync data between private and public clouds, accelerating cloud migrations and customer experience transformations, as well as the adoption of disruptive AI technologies.

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.

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.

Dremio provides lightning-fast queries as well as a self-service semantic layer directly to your data lake storage. No data moving to proprietary data warehouses, and no cubes, aggregation tables, or extracts. Data architects have flexibility and control, while data consumers have self-service. Apache Arrow and Dremio technologies such as Data Reflections, Columnar Cloud Cache(C3), and Predictive Pipelining combine to make it easy to query your data lake storage. An abstraction layer allows IT to apply security and business meaning while allowing analysts and data scientists access data to explore it and create new virtual datasets. Dremio's semantic layers is an integrated searchable catalog that indexes all your metadata so business users can make sense of your data. The semantic layer is made up of virtual datasets and spaces, which are all searchable and indexed.

Standardize your AI governance efforts across different stakeholders, ensure regulatory readiness for your governance processes, and manage and measure your AI compliance and risks. You can transform your AI/ML projects from being managed by a variety of teams and processes into a centralized repository for trusted governance. Keep up-to-date on the latest regulations and standards by downloading AI Policy Packs. These packs meet all current and future regulations. Credo AI is an intelligence layer which sits on top your AI infrastructure and converts technical artifacts to actionable risk and compliance insights for product leaders and data scientists as well as governance teams. Credo AI is an intelligence layer which sits on top your technical and business infrastructure. It converts technical artifacts into compliance scores and risk scores.

The modern data workspace. All your data assets, from data tables to reports, will be instantly discoverable. The combination of powerful search algorithms and easy browsing makes it easy to find the right asset. Atlan automatically generates data quality profiles that make it easy to detect bad data. We have you covered, from automatic variable type detection and frequency distribution to missing values or outlier detection. Atlan takes the hassle out of managing and governing your data ecosystem. Atlan's bots analyze SQL query history to automatically construct data lineage. They also auto-detect PII information. This allows you to create dynamic access policies and best-in-class governance. Our Excel-like query builder allows anyone to query multiple data lakes, warehouses, and DBs. Native integrations with tools such as Tableau and Jupyter make data collaboration possible.

Cloud-native data integration with IBM Cloud Pak data enables you to accelerate AI innovation AI-powered data integration from anywhere. Your AI and analytics can only be as good as the data they are powered by. IBM®, DataStage®, for IBM Cloud Pak®, for Data provides high-quality data through a container-based architecture. It combines industry-leading data integration, DataOps, governance, and analytics on one data and AI platform. Automation speeds up administrative tasks, helping to reduce TCO. AI-based design accelerators, out-of-the box integration with DataOps or data science services accelerate AI innovation. Multicloud integration and parallelism allow you to deliver trusted data across hybrid and multicloud environments. The IBM Cloud Pak for Data platform allows you to manage the data and analytics lifecycle. Data science, event messaging, and data warehousing are some of the services offered. Automated load balancing and parallel engine.

Fiddler is a pioneer in enterprise Model Performance Management. Data Science, MLOps, and LOB teams use Fiddler to monitor, explain, analyze, and improve their models and build trust into AI. The unified environment provides a common language, centralized controls, and actionable insights to operationalize ML/AI with trust. It addresses the unique challenges of building in-house stable and secure MLOps systems at scale. Unlike observability solutions, Fiddler seamlessly integrates deep XAI and analytics to help you grow into advanced capabilities over time and build a framework for responsible AI practices. Fortune 500 organizations use Fiddler across training and production models to accelerate AI time-to-value and scale and increase revenue.

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.

The core technology that enables modern data integration and data management. Connect disparate, structured and unstructured data sources quickly. Catalog your entire data ecosystem. The data is kept in the source and can be accessed whenever needed. Adapt data models to the consumer's needs, even if they come from multiple sources. Your back-end technologies can be hidden from end users. You can secure the virtual model and use it to consume standard SQL and other formats such as SOAP, REST, SOAP, and OData. Access to all types data is easy. Data integration and data modeling capabilities are available. Active Data Catalog and self service capabilities for data and metadata discovery and preparation. Full data security and governance capabilities. Data queries executed quickly and intelligently. Real-time data delivery in all formats. Data marketplaces can be created. Data-driven strategies can be made easier by separating business applications and data systems.

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.

You can now build what took years. Simple, customizable, scalable, secure, ML monitoring. Everything you need to deploy and maintain ML in production. Superwise integrates with any ML stack, and can connect to any number of communication tools. Want to go further? Superwise is API-first. All of our APIs allow you to access everything, and we mean everything. All this from the comfort of your cloud. You have complete control over ML monitoring. You can set up metrics and policies using our SDK and APIs. Or, you can simply choose a template to monitor and adjust the sensitivity, conditions and alert channels. Get Superwise or contact us for more information. Superwise's ML monitoring policy templates allow you to quickly create alerts. You can choose from dozens pre-built monitors, ranging from data drift and equal opportunity, or you can customize policies to include your domain expertise.

Saturn Cloud is a data science and machine learning platform flexible enough for any team supporting Python, R, and more. Scale, collaborate, and utilize built-in management capabilities to aid you when you run your code.

SAP HANA is an in-memory database with high performance that accelerates data-driven decision-making and actions. It supports all workloads and provides the most advanced analytics on multi-model data on premise and in cloud.

Simplified quality assurance for machine learning. Snitch eliminates all noise so you can find the most relevant information to improve your models. With powerful dashboards and analysis, you can track your model's performance beyond accuracy. Identify potential problems in your data pipeline or distribution shifts and fix them before they impact your predictions. Once you've deployed, stay in production and have visibility to your models and data throughout the entire cycle. You can keep your data safe, whether it's cloud, on-prem or private cloud. Use the tools you love to integrate Snitch into your MLops process! We make it easy to get up and running quickly. Sometimes accuracy can be misleading. Before you deploy your models, make sure to assess their robustness and importance. Get actionable insights that will help you improve your models. Compare your models against historical metrics.

A new category of AI. Most AI solutions today are designed using a mathematical and statistical lens. We took a different approach. Intelligent Artifacts' team has created a new type of AI based on information theory. It is a true AGI that eliminates the current shortcomings in machine intelligence. Our framework separates the intelligence layer from the data and application layers, allowing it to learn in real time and allowing it to make predictions down to the root cause. A truly integrated platform is required for AGI. Intelligent Artifacts will allow you to model information, not data. Predictions and decisions can be made across multiple domains without the need for rewriting code. Our dynamic platform and specialized AI consultants will provide you with a tailored solution that quickly provides deep insights and better outcomes from your data.

PolyAnalyst, a data analysis tool, is used by large companies in many industries (Insurance Manufacturing, Finance, etc.). It uses a visual composer to simplify complex data analysis modeling instead of programming/coding. This is one of its most distinctive features. It can combine structured and poly-structured data for unified analysis (multiple-choice questions and open ended responses), and it can process text data from over 16+ languages. PolyAnalyst provides many features to meet comprehensive data analysis requirements, including the ability to load data, cleanse and prepare data for analysis, deploy machine learning and supervised analytics techniques, and create reports that non-analysts may use to uncover insights.

Lyftrondata can help you build a governed lake, data warehouse or migrate from your old database to a modern cloud-based data warehouse. Lyftrondata makes it easy to create and manage all your data workloads from one platform. This includes automatically building your warehouse and pipeline. It's easy to share the data with ANSI SQL, BI/ML and analyze it instantly. You can increase the productivity of your data professionals while reducing your time to value. All data sets can be defined, categorized, and found in one place. These data sets can be shared with experts without coding and used to drive data-driven insights. This data sharing capability is ideal for companies who want to store their data once and share it with others. You can define a dataset, apply SQL transformations, or simply migrate your SQL data processing logic into any cloud data warehouse.

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.

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.

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.

Integrate with existing toolchain to automate self-service provisioning, refresh enterprise workloads, and integrate with existing tools. Through a rich set APIs and automation, data scientists can achieve high-performance data delivery and re-use. Any cloud data can be recovered at any time, at any scale, and beyond legacy solutions. Reduce the business impact of ransomware and cyber attacks by quickly recovering with immutable backups. Unified platform to protect, secure, keep, govern, and recover your data whether it is on-premises or cloud. Actifio's patented software platform turns data silos into data pipelines. Virtual Data Pipeline (VDP), provides full-stack data management - hybrid, on-premises, or multi-cloud -- from rich application integration, SLA based orchestration, flexible movement, data immutability, security, and SLA-based orchestration.

Cloud environments can be quickly set up for quick development, testing, and productivity for your IT staff and business users. Comprehensive data governance for business users will reduce the risks and cost of maintaining your data lakes. You can save money by providing consistent, timely, and clean information for your data lakes, big data projects, and data warehouses. Also, consolidate applications and retire outdated databases. Automatic schema propagation can be used to accelerate job generation, type-ahead searching, and backwards capabilities. All this while designing once and executing everywhere. With a cognitive design that recognizes patterns and suggests ways to use them, you can create data integration flows and enforce quality rules and data governance. You can improve visibility and information governance by creating authoritative views of information that are complete and authoritative.

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.

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.

Accelerate the entire machine learning lifecycle. Developers and data scientists can have more productive experiences building, training, and deploying machine-learning models faster by empowering them. Accelerate time-to-market and foster collaboration with industry-leading MLOps -DevOps machine learning. Innovate on a trusted platform that is secure and trustworthy, which is designed for responsible ML. Productivity for all levels, code-first and drag and drop designer, and automated machine-learning. Robust MLOps capabilities integrate with existing DevOps processes to help manage the entire ML lifecycle. Responsible ML capabilities – understand models with interpretability, fairness, and protect data with differential privacy, confidential computing, as well as control the ML cycle with datasheets and audit trials. Open-source languages and frameworks supported by the best in class, including MLflow and Kubeflow, ONNX and PyTorch. TensorFlow and Python are also supported.

All the steps involved in building machine learning algorithms and predicting results, all in one click. Data Dialog allows you to easily shape your data without having to wrangle your files. Your prediction reports can be shared with your team members or made public. Let anyone make predictions on your model. Our low-code API allows you to integrate dynamic ML predictions directly into your app. Real-time prediction of willingness to pay, score leads, and many other things. AI gives you access to the most advanced algorithms in the world, without compromising on performance. Forecast revenue, optimize supply chain, personalize your marketing. Now you can see what the next steps are. In minutes, you can add a CSV file or integrate with your favorite data sources. Select your prediction column from the dropdown and we'll automatically build the AI. Visualize the top drivers, predicted results, and simulate "what-if?" scenarios.

Datatron provides tools and features that are built from scratch to help you make machine learning in production a reality. Many teams realize that there is more to deploying models than just the manual task. Datatron provides a single platform that manages all your ML, AI and Data Science models in production. We can help you automate, optimize and accelerate your ML model production to ensure they run smoothly and efficiently. Data Scientists can use a variety frameworks to create the best models. We support any framework you use to build a model (e.g. TensorFlow and H2O, Scikit-Learn and SAS are supported. Explore models that were created and uploaded by your data scientists, all from one central repository. In just a few clicks, you can create scalable model deployments. You can deploy models using any language or framework. Your model performance will help you make better decisions.