Cloudera Data Platform Integrations

TensorFlow is a comprehensive open-source machine learning platform that covers the entire process from development to deployment. This platform boasts a rich and adaptable ecosystem featuring various tools, libraries, and community resources, empowering researchers to advance the field of machine learning while allowing developers to create and implement ML-powered applications with ease. With intuitive high-level APIs like Keras and support for eager execution, users can effortlessly build and refine ML models, facilitating quick iterations and simplifying debugging. The flexibility of TensorFlow allows for seamless training and deployment of models across various environments, whether in the cloud, on-premises, within browsers, or directly on devices, regardless of the programming language utilized. Its straightforward and versatile architecture supports the transformation of innovative ideas into practical code, enabling the development of cutting-edge models that can be published swiftly. Overall, TensorFlow provides a powerful framework that encourages experimentation and accelerates the machine learning process.

Docker streamlines tedious configuration processes and is utilized across the entire development lifecycle, facilitating swift, simple, and portable application creation on both desktop and cloud platforms. Its all-encompassing platform features user interfaces, command-line tools, application programming interfaces, and security measures designed to function cohesively throughout the application delivery process. Jumpstart your programming efforts by utilizing Docker images to craft your own distinct applications on both Windows and Mac systems. With Docker Compose, you can build multi-container applications effortlessly. Furthermore, it seamlessly integrates with tools you already use in your development workflow, such as VS Code, CircleCI, and GitHub. You can package your applications as portable container images, ensuring they operate uniformly across various environments, from on-premises Kubernetes to AWS ECS, Azure ACI, Google GKE, and beyond. Additionally, Docker provides access to trusted content, including official Docker images and those from verified publishers, ensuring quality and reliability in your application development journey. This versatility and integration make Docker an invaluable asset for developers aiming to enhance their productivity and efficiency.

Amazon Simple Storage Service (Amazon S3) is a versatile object storage solution that provides exceptional scalability, data availability, security, and performance. It accommodates clients from various sectors, enabling them to securely store and manage any volume of data for diverse applications, including data lakes, websites, mobile apps, backups, archiving, enterprise software, IoT devices, and big data analytics. With user-friendly management tools, Amazon S3 allows users to effectively organize their data and set tailored access permissions to satisfy their unique business, organizational, and compliance needs. Offering an impressive durability rate of 99.999999999% (11 nines), it supports millions of applications for businesses globally. Businesses can easily adjust their storage capacity to match changing demands without needing upfront investments or lengthy resource acquisition processes. Furthermore, the high durability ensures that data remains safe and accessible, contributing to operational resilience and peace of mind for organizations.

Companies of all sizes can utilize object storage to manage any volume of data seamlessly. You can retrieve your data as frequently as needed, and with Object Lifecycle Management (OLM), you can set criteria for your data to automatically move to more affordable storage options, such as based on its age or the presence of a newer version. Cloud Storage offers an expanding array of locations for storage buckets, along with various automatic redundancy choices to ensure the safety of your data. Whether your priority is achieving rapid response times or developing a comprehensive disaster recovery strategy, you have the flexibility to tailor your data storage solutions to your specific needs. Additionally, the Storage Transfer Service and Transfer Service for on-premises data provide efficient online methods for moving data to Cloud Storage, equipped with the scalability and speed necessary for a streamlined transfer experience. For those who prefer offline data movement, the Transfer Appliance serves as a portable storage server that can be shipped directly to your location. This combination of services allows businesses to enhance their data management strategies effectively.

Apache Hive is a data warehouse solution that enables the efficient reading, writing, and management of substantial datasets stored across distributed systems using SQL. It allows users to apply structure to pre-existing data in storage. To facilitate user access, it comes equipped with a command line interface and a JDBC driver. As an open-source initiative, Apache Hive is maintained by dedicated volunteers at the Apache Software Foundation. Initially part of the Apache® Hadoop® ecosystem, it has since evolved into an independent top-level project. We invite you to explore the project further and share your knowledge to enhance its development. Users typically implement traditional SQL queries through the MapReduce Java API, which can complicate the execution of SQL applications on distributed data. However, Hive simplifies this process by offering a SQL abstraction that allows for the integration of SQL-like queries, known as HiveQL, into the underlying Java framework, eliminating the need to delve into the complexities of the low-level Java API. This makes working with large datasets more accessible and efficient for developers.

Our platform allows businesses to use data, including its application in advanced analysis, machine learning and AI, to do great things without worrying that customers, employees or intellectual property are at risk. The Protegrity Data Protection Platform does more than just protect data. It also classifies and discovers data, while protecting it. It is impossible to protect data you don't already know about. Our platform first categorizes data, allowing users the ability to classify the type of data that is most commonly in the public domain. Once those classifications are established, the platform uses machine learning algorithms to find that type of data. The platform uses classification and discovery to find the data that must be protected. The platform protects data behind many operational systems that are essential to business operations. It also provides privacy options such as tokenizing, encryption, and privacy methods.

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.

At Progress DataDirect, we are passionate about enhancing applications through enterprise data. Our solutions for data connectivity cater to both cloud and on-premises environments, encompassing a wide range of sources such as relational databases, NoSQL, Big Data, and SaaS. We prioritize performance, reliability, and security, which are integral to our designs for numerous enterprises and prominent analytics, BI, and data management vendors. By utilizing our extensive portfolio of high-value connectors, you can significantly reduce your development costs across diverse data sources. Our commitment to customer satisfaction includes providing 24/7 world-class support and robust security measures to ensure peace of mind. Experience the convenience of our affordable, user-friendly drivers that facilitate quicker SQL access to your data. As a frontrunner in the data connectivity sector, we are dedicated to staying ahead of industry trends. If you happen to need a specific connector that we have not yet created, don't hesitate to contact us, and we will assist you in developing an effective solution. It's our mission to seamlessly embed connectivity into your applications or services, enhancing their overall functionality.

The rise of data-driven decision-making has resulted in a significant increase in business data and a heightened demand for its analysis. This phenomenon is prompting IT departments to transition from costly Enterprise Data Warehouses (EDW) to more economical Big Data platforms such as Hadoop or AWS, which boast a Total Cost of Ownership (TCO) that is approximately ten times less. Nevertheless, these new systems are not particularly suited for interactive business intelligence (BI) applications, as they struggle to provide the same level of performance and user concurrency that traditional EDWs offer. To address this shortcoming, Jethro was created. It serves customers by enabling interactive BI on Big Data without necessitating any modifications to existing applications or data structures. Jethro operates as a seamless middle tier, requiring no maintenance and functioning independently. Furthermore, it is compatible with various BI tools like Tableau, Qlik, and Microstrategy, while also being agnostic to data sources. By fulfilling the needs of business users, Jethro allows thousands of concurrent users to efficiently execute complex queries across billions of records, enhancing overall productivity and decision-making capabilities. This innovative solution represents a significant advancement in the field of data analytics.

Create rich, interactive dashboards to accelerate your analytical insights throughout your enterprise. Cloudera Data Visualization allows data engineers, data scientists, and business analysts to explore data, collaborate and share insights throughout the data lifecycle - from data ingest through to data insights. Data Visualization, a native Cloudera product, provides a consistent data visualization experience that is easy to use. It includes drag-and drop dashboards and custom applications. SDX provides full security for Data Visualization, enabling enhanced data workflows in all your data and analytics workflows. Cloudera Machine Learning can be used to build predictive applications, or you can leverage your data warehouse for fast intelligent reporting.

The Apache Hadoop software library serves as a framework for the distributed processing of extensive data sets across computer clusters, utilizing straightforward programming models. It is built to scale from individual servers to thousands of machines, each providing local computation and storage capabilities. Instead of depending on hardware for high availability, the library is engineered to identify and manage failures within the application layer, ensuring that a highly available service can run on a cluster of machines that may be susceptible to disruptions. Numerous companies and organizations leverage Hadoop for both research initiatives and production environments. Users are invited to join the Hadoop PoweredBy wiki page to showcase their usage. The latest version, Apache Hadoop 3.3.4, introduces several notable improvements compared to the earlier major release, hadoop-3.2, enhancing its overall performance and functionality. This continuous evolution of Hadoop reflects the growing need for efficient data processing solutions in today's data-driven landscape.

Fully compatible with Netezza, this solution offers a streamlined command-line upgrade option. It can be deployed on-premises, in the cloud, or through a hybrid model. The IBM® Netezza® Performance Server for IBM Cloud Pak® for Data serves as a sophisticated platform for data warehousing and analytics, catering to both on-premises and cloud environments. With significant improvements in in-database analytics functions, this next-generation Netezza empowers users to engage in data science and machine learning with datasets that can reach petabyte levels. It includes features for detecting failures and ensuring rapid recovery, making it robust for enterprise use. Users can upgrade existing systems using a single command-line interface. The platform allows for querying multiple systems as a cohesive unit. You can select the nearest data center or availability zone, specify the desired compute units and storage capacity, and initiate the setup seamlessly. Furthermore, the IBM® Netezza® Performance Server is accessible on IBM Cloud®, Amazon Web Services (AWS), and Microsoft Azure, and it can also be implemented on a private cloud, all powered by the capabilities of IBM Cloud Pak for Data System. This flexibility enables organizations to tailor the deployment to their specific needs and infrastructure.

Monitor user interactions through advanced analytics and categorize users according to their activities. Develop engagement tactics using cutting-edge AI technology. Certain mobile manufacturers impose OS/Device level limitations, which can impede the delivery of push notifications. Our solution enables you to circumvent these barriers, allowing you to connect with an additional 20% of users effectively. We guarantee improved inbox delivery rates by collaborating with email consultants and industry specialists to provide you with optimal strategies. Refrain from sending mass messages that may land in spam folders or damage your brand's integrity. Easily tailor your communications by language for a more personalized approach. Our platform is designed with multilingual capabilities, enabling you to communicate with customers in their native language. Identify users based on acquisition sources, uninstall trends, and more. Customize user segments to fit your specific needs. Foster conversations, lower churn rates, and leverage impactful insights to enhance your overall strategy. With these tools, your potential for user engagement can significantly increase, driving better results for your business.

Efficiently assign, monitor, and execute tasks while gaining valuable insights into productivity. Automate over 100 tasks to enhance human interactions through bots, group chats, and additional tools. Provide actionable insights that empower Line Managers, HR Professionals, and CXOs to maximize their effectiveness. Establish an organizational structure by defining roles and permissions while managing access rights. Oversee the entire employee life cycle, from onboarding to exit, including the publication of necessary documentation. Ensure smooth payroll processing, manage loans and reimbursements, and comply with regulatory requirements. Utilize real-time attendance tracking to manage attendance, holiday calendars, shifts, and integration seamlessly. Achieve organizational objectives and elevate performance through comprehensive 360-degree feedback mechanisms. Enhance employee morale and foster engagement with specialized tools designed for this purpose. Additionally, use engagement tools to create a supportive work environment that drives both productivity and satisfaction.

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

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

R Systems strives to empower businesses to recognize and address obstacles in the customer journey, ultimately enhancing loyalty and long-term profitability by leveraging cutting-edge technologies such as AI, data analytics, Natural Language Processing (NLP), and Deep Neural Networks (DNN). By grasping the core of customer experience, organizations can elevate how their audience engages with their brand, fostering greater loyalty and retention. To achieve this, companies must utilize precise data and metrics to identify, collect, and scrutinize customer information, enabling them to derive actionable insights and make informed decisions aimed at retaining and attracting customers. Our comprehensive data analytics framework is designed to enhance First Contact Resolution (FCR), minimize customer effort, streamline self-service alternatives, and efficiently manage seasonal demand fluctuations. With R Systems as your partner, each interaction will progressively enhance your overall customer experience. In addition, our services facilitate the collection of data from customer engagements, allowing for deeper insights into their behaviors and preferences, which can guide future strategies for improvement.

The Azure Marketplace serves as an extensive digital storefront, granting users access to a vast array of certified, ready-to-use software applications, services, and solutions provided by both Microsoft and various third-party vendors. This platform allows businesses to easily explore, purchase, and implement software solutions directly within the Azure cloud ecosystem. It features a diverse selection of products, encompassing virtual machine images, AI and machine learning models, developer tools, security features, and applications tailored for specific industries. With various pricing structures, including pay-as-you-go, free trials, and subscriptions, Azure Marketplace makes the procurement process more straightforward and consolidates billing into a single Azure invoice. Furthermore, its seamless integration with Azure services empowers organizations to bolster their cloud infrastructure, streamline operational workflows, and accelerate their digital transformation goals effectively. As a result, businesses can leverage cutting-edge technology solutions to stay competitive in an ever-evolving market.

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.

YARN's core concept revolves around the division of resource management and job scheduling/monitoring into distinct daemons, aiming for a centralized ResourceManager (RM) alongside individual ApplicationMasters (AM) for each application. Each application can be defined as either a standalone job or a directed acyclic graph (DAG) of jobs. Together, the ResourceManager and NodeManager create the data-computation framework, with the ResourceManager serving as the primary authority that allocates resources across all applications in the environment. Meanwhile, the NodeManager acts as the local agent on each machine, overseeing containers and tracking their resource consumption, including CPU, memory, disk, and network usage, while also relaying this information back to the ResourceManager or Scheduler. The ApplicationMaster functions as a specialized library specific to its application, responsible for negotiating resources with the ResourceManager and coordinating with the NodeManager(s) to efficiently execute and oversee the execution of tasks, ensuring optimal resource utilization and job performance throughout the process. This separation allows for more scalable and efficient management in complex computing environments.

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.

Cloudera DataFlow for the Public Cloud (CDF-PC) is a versatile, cloud-based data distribution solution that utilizes Apache NiFi, enabling developers to seamlessly connect to diverse data sources with varying structures, process that data, and deliver it to a wide array of destinations. This platform features a flow-oriented low-code development approach that closely matches the preferences of developers when creating, developing, and testing their data distribution pipelines. CDF-PC boasts an extensive library of over 400 connectors and processors that cater to a broad spectrum of hybrid cloud services, including data lakes, lakehouses, cloud warehouses, and on-premises sources, ensuring efficient and flexible data distribution. Furthermore, the data flows created can be version-controlled within a catalog, allowing operators to easily manage deployments across different runtimes, thereby enhancing operational efficiency and simplifying the deployment process. Ultimately, CDF-PC empowers organizations to harness their data effectively, promoting innovation and agility in data management.