Alternatives to IBM Analytics for Apache Spark

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

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.

You can use your favorite debugging software to locally troubleshoot your Kubernetes services. Telepresence, an open-source tool, allows you to run one service locally and connect it to a remote Kubernetes cluster. Telepresence was initially developed by Ambassador Labs, which creates open-source development tools for Kubernetes such as Ambassador and Forge. We welcome all contributions from the community. You can help us by submitting an issue, pull request or reporting a bug. Join our active Slack group to ask questions or inquire about paid support plans. Telepresence is currently under active development. Register to receive updates and announcements. You can quickly debug locally without waiting for a container to be built/push/deployed. Ability to use their favorite local tools such as debugger, IDE, etc. Ability to run large-scale programs that aren't possible locally.

Improvado, an ETL solution, facilitates data pipeline automation for marketing departments without any technical skills. This platform supports marketers in making data-driven, informed decisions. It provides a comprehensive solution for integrating marketing data across an organization. Improvado extracts data form a marketing data source, normalizes it and seamlessly loads it into a marketing dashboard. It currently has over 200 pre-built connectors. On request, the Improvado team will create new connectors for clients. Improvado allows marketers to consolidate all their marketing data in one place, gain better insight into their performance across channels, analyze attribution models, and obtain accurate ROMI data. Companies such as Asus, BayCare and Monster Energy use Improvado to mark their markes.

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

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.

Microsoft Azure serves as a versatile cloud computing platform that facilitates swift and secure development, testing, and management of applications. With Azure, you can innovate purposefully, transforming your concepts into actionable solutions through access to over 100 services that enable you to build, deploy, and manage applications in various environments—be it in the cloud, on-premises, or at the edge—utilizing your preferred tools and frameworks. The continuous advancements from Microsoft empower your current development needs while also aligning with your future product aspirations. Committed to open-source principles and accommodating all programming languages and frameworks, Azure allows you the freedom to build in your desired manner and deploy wherever it suits you best. Whether you're operating on-premises, in the cloud, or at the edge, Azure is ready to adapt to your current setup. Additionally, it offers services tailored for hybrid cloud environments, enabling seamless integration and management. Security is a foundational aspect, reinforced by a team of experts and proactive compliance measures that are trusted by enterprises, governments, and startups alike. Ultimately, Azure represents a reliable cloud solution, backed by impressive performance metrics that validate its trustworthiness. This platform not only meets your needs today but also equips you for the evolving challenges of tomorrow.

AWS Elastic Beanstalk offers a user-friendly platform for deploying and scaling web applications and services built using various programming languages such as Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker, utilizing well-known servers like Apache, Nginx, Passenger, and IIS. By merely uploading your code, Elastic Beanstalk takes care of the entire deployment process, which includes capacity provisioning, load balancing, auto-scaling, and monitoring application health. Importantly, you maintain complete control over the AWS resources that support your application and can access the underlying infrastructure whenever necessary. There is no extra cost associated with Elastic Beanstalk itself; you are charged solely for the AWS resources required to store and operate your applications. Notably, Elastic Beanstalk is considered the quickest and most straightforward method for deploying your application on AWS. You can effortlessly upload your application using the AWS Management Console, a Git repository, or an integrated development environment (IDE) like Eclipse or Visual Studio, ensuring a seamless integration into your workflow. This flexibility allows developers to focus on coding rather than worrying about the intricacies of deployment.

Kubernetes serves as a powerful foundation for transformative ideas. It enables developers to innovate and deliver projects more rapidly through the premier hybrid cloud and enterprise container solution. Red Hat OpenShift simplifies the process with automated installations, updates, and comprehensive lifecycle management across the entire container ecosystem, encompassing the operating system, Kubernetes, cluster services, and applications on any cloud platform. This service allows teams to operate with speed, flexibility, assurance, and a variety of options. You can code in production mode wherever you prefer to create, enabling a return to meaningful work. Emphasizing security at all stages of the container framework and application lifecycle, Red Hat OpenShift provides robust, long-term enterprise support from a leading contributor to Kubernetes and open-source technology. It is capable of handling the most demanding workloads, including AI/ML, Java, data analytics, databases, and more. Furthermore, it streamlines deployment and lifecycle management through a wide array of technology partners, ensuring that your operational needs are met seamlessly. This integration of capabilities fosters an environment where innovation can thrive without compromise.

If you're in need of computing power, database solutions, content distribution, or various other functionalities, AWS offers a wide array of services designed to assist you in developing advanced applications with enhanced flexibility, scalability, and reliability. Amazon Web Services (AWS) stands as the most extensive and widely utilized cloud platform globally, boasting over 175 fully functional services spread across data centers worldwide. A diverse range of customers, from rapidly expanding startups to major corporations and prominent government bodies, are leveraging AWS to reduce expenses, enhance agility, and accelerate innovation. AWS provides a larger selection of services, along with more features within those services, compared to any other cloud provider—covering everything from fundamental infrastructure technologies like computing, storage, and databases to cutting-edge innovations such as machine learning, artificial intelligence, data lakes, analytics, and the Internet of Things. This breadth of offerings facilitates a quicker, simpler, and more cost-effective transition of your current applications to the cloud, ensuring that you can stay ahead in a competitive landscape while taking advantage of the latest technological advancements.

BDB is an advanced platform for data analytics and business intelligence that excels in extracting valuable insights from your data. It can be implemented both in cloud environments and on-premises. With a unique microservices architecture, it incorporates components for Data Preparation, Predictive Analytics, Pipelines, and Dashboard design, enabling tailored solutions and scalable analytics across various sectors. Thanks to its robust NLP-driven search functionality, users can harness the potential of data seamlessly across desktops, tablets, and mobile devices. BDB offers numerous integrated data connectors, allowing it to interface with a wide array of popular data sources, applications, third-party APIs, IoT devices, and social media platforms in real-time. It facilitates connections to relational databases, big data systems, FTP/SFTP servers, flat files, and web services, effectively managing structured, semi-structured, and unstructured data. Embark on your path to cutting-edge analytics today, and discover the transformative power of BDB for your organization.

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

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.

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.

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.

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

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.

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.

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.

Oracle Cloud Infrastructure (OCI) Data Flow is a comprehensive managed service for Apache Spark, enabling users to execute processing tasks on enormous data sets without the burden of deploying or managing infrastructure. This capability accelerates the delivery of applications, allowing developers to concentrate on building their apps rather than dealing with infrastructure concerns. OCI Data Flow autonomously manages the provisioning of infrastructure, network configurations, and dismantling after Spark jobs finish. It also oversees storage and security, significantly reducing the effort needed to create and maintain Spark applications for large-scale data analysis. Furthermore, with OCI Data Flow, there are no clusters that require installation, patching, or upgrading, which translates to both time savings and reduced operational expenses for various projects. Each Spark job is executed using private dedicated resources, which removes the necessity for prior capacity planning. Consequently, organizations benefit from a pay-as-you-go model, only incurring costs for the infrastructure resources utilized during the execution of Spark jobs. This innovative approach not only streamlines the process but also enhances scalability and flexibility for data-driven applications.

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.

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

Effortlessly extract, transform, and load (ETL) data for analytics and data science applications. Create seamless, code-free data flows directed towards data lakes and data marts. This functionality is included within Oracle’s extensive suite of integration tools. The user-friendly interface allows for easy configuration of integration parameters and automates the mapping of data between various sources and targets. You can utilize pre-built operators like joins, aggregates, or expressions to effectively manipulate your data. Central management of your processes enables the use of parameters to adjust specific configuration settings during runtime. Users can actively prepare their datasets and observe transformation results in real-time for process validation. Enhance your productivity and adjust data flows instantly, without needing to wait for execution completion. Additionally, this solution helps prevent broken integration flows and minimizes maintenance challenges as data schemas change over time, ensuring a smooth data management experience. This capability empowers users to focus on gaining insights from their data rather than grappling with technical difficulties.

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.

Investing in the appropriate technology at the optimal moments and on the suitable platforms is essential for fostering innovation, enhancing customer loyalty, and expanding your business. Achieve the results you desire by harnessing cloud technology the right way, which can yield up to three times the return on investment while delivering quicker outcomes at lower costs, risks, and disruptions. DXC is here to guide you in making informed choices regarding application migration to the cloud and the timing for these transitions. With DXC Cloud services, you can fully leverage your data while maintaining a secure environment. Our expertise in managing hybrid IT systems for some of the largest corporations globally demonstrates our understanding of the critical role cloud computing plays in essential IT operations. Annually, our cloud migration services facilitate the transition of 65,000 workloads to the cloud, and we have successfully modernized numerous mainframe systems and transitioned over 15,000 applications. Let us support you in defining, executing, and overseeing your cloud strategy effectively. Collaborate with DXC to ensure your cloud journey is executed flawlessly and to its full potential. Together, we can create a robust digital foundation that propels your business forward.

CodeNOW is the DevOps platform for businesses that want to deliver software with the efficiency, frequency, and reliability of digital leaders—without the large IT investments and the distraction from their core business. CodeNOW is listed by Gartner as a DevOps Value Stream Delivery Platform (DevOps VSDP)—category mainstream in 2023 according to Gartner. CodeNOW is cloud-native, cloud-agnostic and covers the full software delivery life cycle by integrating 40 battle-tested open-source solutions (Gitlab, Swagger, Karate, SonarQube, Nexus, Tekton, ArgoCD, Kubernetes, Docker, Helm, Istio, Jenkins, Terraform, and more). CodeNOW users experience no vendor lock-in nor maintenance costs (PaaS model). They do more with the team they already have vs. recruiting of extra expensive, hard-to-find DevOps engineers. With infrastructure abstracted and automated away in the platform, DevOps and Ops teams report freeing time to focus back again on business and operations metrics instead of repetitive delivery tasks. Dev teams can take end-to-end ownership of their own software, from coding requirements to delivering and operating it in the cloud. Developers describe a higher sense of fulfillment, a faster feedback cycle and improved flow.

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.

Dataproc enhances the speed, simplicity, and security of open source data and analytics processing in the cloud. You can swiftly create tailored OSS clusters on custom machines to meet specific needs. Whether your project requires additional memory for Presto or GPUs for machine learning in Apache Spark, Dataproc facilitates the rapid deployment of specialized clusters in just 90 seconds. The platform offers straightforward and cost-effective cluster management options. Features such as autoscaling, automatic deletion of idle clusters, and per-second billing contribute to minimizing the overall ownership costs of OSS, allowing you to allocate your time and resources more effectively. Built-in security measures, including default encryption, guarantee that all data remains protected. With the JobsAPI and Component Gateway, you can easily manage permissions for Cloud IAM clusters without the need to configure networking or gateway nodes, ensuring a streamlined experience. Moreover, the platform's user-friendly interface simplifies the management process, making it accessible for users at all experience levels.

Two complementary tools, one enterprise-grade platform. Open source KNIME Analytics Platform to create data science. Commercial KNIME Server to produce data science. KNIME Analytics Platform is an open-source software that creates data science. KNIME is intuitive, open, and constantly integrating new developments. It makes data science and designing data science workflows as easy as possible. KNIME Server Enterprise Software is used to facilitate team-based collaboration, automation, and management of data science workflows, as well as the deployment and management of analytical applications and services. Non-experts have access to KNIME WebPortal and REST APIs. Extensions for KNIME Analytics Platform allow you to do more with your data. Some are created and maintained by KNIME, while others are contributed by the community or our trusted partners. Integrations are also available with many open-source projects.

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.

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.

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

Talend Data Integration allows you to connect and manage all of your data regardless of where it is located. Connect virtually any data source to any data environment using over 1,000 connectors and component. Drag-and-drop interface makes it easy to create and deploy reusable data pipes. It's 10x faster than hand-coding. Talend has been a leader in scaling large data sets to advanced data analytics and Spark platforms. We partner with top cloud service providers, data warehouses and analytics platforms such as Amazon Web Services, Microsoft Azure and Google Cloud Platform, Snowflake and Databricks. Talend ensures data quality at every stage of data integration. Before inconsistencies disrupt or impact critical decisions, you can identify, highlight, and fix them as data moves through your systems. Connect to data wherever it is, and use it where you want it.

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

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.

Hex unites the finest features of notebooks, business intelligence, and documentation into a cohesive and collaborative user interface, establishing itself as a contemporary Data Workspace. It simplifies the process of connecting to various data sources and allows for collaborative analysis via SQL and Python-based notebooks, enabling users to share their findings as interactive data applications and narratives. Upon entering Hex, the Projects page serves as the default landing area, making it easy to access both your own projects and those shared within your workspace. The outline feature offers a streamlined overview of all cells contained in a project's Logic View, where each cell is annotated with the variables it defines. Furthermore, cells that produce visible outputs—such as chart cells, input parameters, and markdown cells—provide a preview of their results. By clicking on any cell within the outline, users can instantly navigate to that specific location in the logic, enhancing the overall efficiency of the workflow. This functionality ensures that collaboration and data exploration are both intuitive and effective.

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

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

Istio is an innovative open-source technology that enables developers to effortlessly connect, manage, and secure various microservices networks, irrespective of the platform, origin, or vendor. With a rapidly increasing number of contributors on GitHub, Istio stands out as one of the most prominent open-source initiatives, bolstered by a robust community. IBM takes pride in being a founding member and significant contributor to the Istio project, actively leading its Working Groups. On the IBM Cloud Kubernetes Service, Istio is available as a managed add-on, seamlessly integrating with your Kubernetes cluster. With just one click, users can deploy a well-optimized, production-ready instance of Istio on their IBM Cloud Kubernetes Service cluster, which includes essential core components along with tools for tracing, monitoring, and visualization. This streamlined process ensures that all Istio components are regularly updated by IBM, which also oversees the lifecycle of the control-plane components, providing users with a hassle-free experience. As microservices continue to evolve, Istio's role in simplifying their management becomes increasingly vital.

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.

The SAP Business Technology Platform (BTP) serves as an all-encompassing solution designed to enable organizations to seamlessly integrate, analyze, and create applications with a significant emphasis on artificial intelligence, automation, and efficient data management. By simplifying business processes for both SAP and non-SAP applications, it provides robust features like generative AI, real-time analytics, and data-informed application development. With SAP BTP, companies can accelerate their development efforts and ensure smooth integration thanks to pre-built workflows and AI models that boost overall productivity. This platform allows organizations to construct more intelligent applications, streamline workflows, and devise dependable AI solutions that foster innovation and hasten the realization of value, ultimately transforming the way businesses operate. Additionally, the versatility of SAP BTP ensures that companies can adapt to evolving market demands and stay competitive in a rapidly changing landscape.

Dataphin is crafted to assist users in developing and overseeing intelligent, cohesive data assets while fostering innovation. It serves as a comprehensive all-in-one platform that encompasses data integration, warehouse modeling, identity and profile creation, asset management, and various data services. Through Dataphin's integration capabilities, users can consolidate their organization’s data assets from diverse computing and storage environments, utilizing warehousing services to streamline the design and development of data warehouses. Additionally, the distilling service allows users to generate detailed profiles for uniquely identifiable business entities, including customers and products. The asset management feature oversees the entire spectrum of the organization’s data assets, enabling users to effortlessly search for information, ensure optimal data application performance, and analyze data costs for better management. Furthermore, Dataphin’s data service module includes a query interface and APIs that facilitate analytics and support a variety of SaaS-based data applications, enhancing overall user experience and operational efficiency. With its multifaceted capabilities, Dataphin empowers businesses to harness their data assets effectively and drive innovation forward.

Cloud Foundry simplifies and accelerates the processes of building, testing, deploying, and scaling applications while offering a variety of cloud options, developer frameworks, and application services. As an open-source initiative, it can be accessed through numerous private cloud distributions as well as public cloud services. Featuring a container-based architecture, Cloud Foundry supports applications written in multiple programming languages. You can deploy applications to Cloud Foundry with your current tools and without needing to alter the code. Additionally, CF BOSH allows you to create, deploy, and manage high-availability Kubernetes clusters across any cloud environment. By separating applications from the underlying infrastructure, users have the flexibility to determine the optimal hosting solutions for their workloads—be it on-premises, public clouds, or managed infrastructures—and can relocate these workloads swiftly, typically within minutes, without any modifications to the applications themselves. This level of flexibility enables businesses to adapt quickly to changing needs and optimize resource usage effectively.

You need the flexibility and control to create innovative digital experiences. You can eliminate the need to manage and build core infrastructure. Instantly create an application clone of every Git branch for quick updates, testing, and deployment to production. Automated deployments, stable environments and a consistent development process are all possible without having to manage infrastructure. You can solve multiple customer problems across industries and geographies by leveraging a single global, secure cloud infrastructure. You can create amazing websites and web applications in the languages and frameworks you choose. You can deploy complex architectures in seconds. All the services you require are included, so you can innovate faster. Instead of focusing on infrastructure, focus on solving customer problems.