Hadoop Integrations

Effortlessly load your data into or extract it from Hadoop and data lakes, ensuring it is primed for generating reports, visualizations, or conducting advanced analytics—all within the data lakes environment. This streamlined approach allows you to manage, transform, and access data stored in Hadoop or data lakes through a user-friendly web interface, minimizing the need for extensive training. Designed specifically for big data management on Hadoop and data lakes, this solution is not simply a rehash of existing IT tools. It allows for the grouping of multiple directives to execute either concurrently or sequentially, enhancing workflow efficiency. Additionally, you can schedule and automate these directives via the public API provided. The platform also promotes collaboration and security by enabling the sharing of directives. Furthermore, these directives can be invoked from SAS Data Integration Studio, bridging the gap between technical and non-technical users. It comes equipped with built-in directives for various tasks, including casing, gender and pattern analysis, field extraction, match-merge, and cluster-survive operations. For improved performance, profiling processes are executed in parallel on the Hadoop cluster, allowing for the seamless handling of large datasets. This comprehensive solution transforms the way you interact with data, making it more accessible and manageable than ever.

Combine master data management solutions with those found in SAS 9.4, where SAS MDM operates as a web-based interface accessible via the SAS Data Management Console. This system delivers a cohesive and precise representation of organizational data by consolidating information from multiple sources into a singular master record. Additionally, SAS® Data Remediation and SAS® Task Manager synergistically enhance SAS MDM's capabilities, as well as those of other SAS products, including SAS® Data Management and SAS® Data Quality. Through SAS Data Remediation, users can address and rectify issues arising from business rules in both batch jobs and real-time processes within SAS MDM. Meanwhile, SAS Task Manager serves as a supportive tool that integrates seamlessly with SAS Workflow technologies, allowing users to manage workflows initiated by other SAS applications with ease. By enabling the initiation, cessation, and transition of workflows uploaded to the SAS Workflow server, this ecosystem empowers organizations to maintain efficient data management practices. Overall, the integration of these technologies creates a robust framework for handling master data effectively.

The Knox API Gateway functions as a reverse proxy, prioritizing flexibility in policy enforcement and backend service management for the requests it handles. It encompasses various aspects of policy enforcement, including authentication, federation, authorization, auditing, dispatch, host mapping, and content rewriting rules. A chain of providers, specified in the topology deployment descriptor associated with each Apache Hadoop cluster secured by Knox, facilitates this policy enforcement. Additionally, the cluster definition within the descriptor helps the Knox Gateway understand the structure of the cluster, enabling effective routing and translation from user-facing URLs to the internal workings of the cluster. Each secured Apache Hadoop cluster is equipped with its own REST APIs, consolidated under a unique application context path. Consequently, the Knox Gateway can safeguard numerous clusters while offering REST API consumers a unified endpoint for seamless access. This design enhances both security and usability by simplifying interactions with multiple backend services.

Enhance investigative processes and boost analyst efficiency with an advanced XDR Cybersecurity Solution. The Respond Analyst™, powered by an XDR Engine, streamlines the identification of security threats by transforming resource-heavy monitoring and initial assessments into detailed and uniform investigations. In contrast to other XDR solutions, the Respond Analyst employs probabilistic mathematics and integrated reasoning to connect various pieces of evidence, effectively evaluating the likelihood of malicious and actionable events. By doing so, it significantly alleviates the workload on security operations teams, allowing them to spend more time on proactive threat hunting rather than chasing down false positives. Furthermore, the Respond Analyst enables users to select top-tier controls to enhance their sensor infrastructure. It also seamlessly integrates with leading security vendor solutions across key areas like EDR, IPS, web filtering, EPP, vulnerability scanning, authentication, and various other categories, ensuring a comprehensive defense strategy. With such capabilities, organizations can expect not only improved response times but also a more robust security posture overall.

Our security controls, driven by data science, facilitate the automation of advanced threat detection, remediation, and response. Gurucul’s Unified Security and Risk Analytics platform addresses the crucial question: Is anomalous behavior truly a risk? This unique capability sets us apart in the industry. We prioritize your time by avoiding alerts related to non-risky anomalous activities. By leveraging context, we can accurately assess whether certain behaviors pose a risk, as understanding the context is essential. Merely reporting what is occurring lacks value; instead, we emphasize notifying you when a genuine threat arises, which exemplifies the Gurucul advantage. This actionable information empowers your decision-making. Our platform effectively harnesses your data, positioning us as the only security analytics provider capable of seamlessly integrating all your data from the outset. Our enterprise risk engine can absorb data from various sources, including SIEMs, CRMs, electronic medical records, identity and access management systems, and endpoints, ensuring comprehensive threat analysis. We’re committed to maximizing the potential of your data to enhance security.

OpenText Data Privacy & Protection Foundation (Voltage) enables organizations to secure sensitive information with a modern, quantum-resilient approach that supports both operational continuity and regulatory compliance. Instead of relying on traditional encryption that breaks workflows, it uses NIST-approved, format-preserving methods that preserve data usability while protecting high-value fields. The platform provides persistent protection, securing data no matter where it lives or how it moves—across cloud infrastructures, analytics pipelines, and distributed applications. With stateless key management, performance stays high even at massive volumes, making it ideal for enterprise-scale deployments. Global organizations trust OpenText because its technologies meet stringent certifications, including FIPS 140-2, Common Criteria, and NIST SP 800-38G. Deep integrations across AWS, Azure, Google Cloud, Snowflake, Hadoop, Databricks, and more ensure seamless adoption without architectural overhaul. This enables businesses to modernize, migrate, or analyze data safely without exposing sensitive information. Ultimately, the platform helps reduce compliance risk, streamline governance, and future-proof data protection strategies.

Mage™ offers comprehensive Static Data Masking (SDM) and Test Data Management (TDM) functionalities that are fully compatible with Imperva’s Data Security Fabric (DSF), ensuring robust safeguarding of sensitive or regulated information. This integration occurs smoothly within an organization’s current IT infrastructure and aligns with existing application development, testing, and data processes, all without necessitating any alterations to the existing architectural setup. As a result, organizations can enhance their data security while maintaining operational efficiency.

The Mage™ Dynamic Data Masking module, part of the Mage data security platform, has been thoughtfully crafted with a focus on the needs of end customers. Developed in collaboration with clients, Mage™ Dynamic Data Masking effectively addresses their unique requirements and challenges. Consequently, this solution has advanced to accommodate virtually every potential use case that enterprises might encounter. Unlike many competing products that often stem from acquisitions or cater to niche scenarios, Mage™ Dynamic Data Masking is designed to provide comprehensive protection for sensitive data accessed by application and database users in production environments. Additionally, it integrates effortlessly into an organization’s existing IT infrastructure, eliminating the need for any substantial architectural modifications, thus ensuring a smoother transition for businesses implementing this solution. This strategic approach reflects a commitment to enhancing data security while prioritizing user experience and operational efficiency.

Real Identity™ provides rapid, sub-second decision-making capabilities that facilitate timely and relevant messaging. This innovative platform empowers leading global brands to accurately identify individuals and ethically engage with them at any location and time, thereby fostering significant experiences. With the ability to connect with audiences at scale and with precision, brands can enhance every customer interaction. Additionally, Real Identity allows companies to effectively manage their identity systems by utilizing five decades of expertise in data and identity, coupled with cutting-edge artificial intelligence and machine learning methodologies. In the fast-paced adtech sector, swift access to identity and data is essential for enabling personalization and informed decision-making. As the landscape evolves away from cookies, first-party data signals will become crucial for driving these initiatives, ensuring that communication remains vibrant between individuals, brands, and publishers. By crafting impactful experiences across all channels, businesses can not only impress current customers and prospects but also maintain compliance with regulations and outpace their competitors. Ultimately, Real Identity™ positions brands to thrive in a dynamic environment while enhancing their customer engagement strategies.

Complexity is the enemy of security. Simplify and scale fine-grained data access control. Dynamically authorize and audit every query to comply with data security and privacy regulations. Okera integrates seamlessly into your infrastructure – in the cloud, on premise, and with cloud-native and legacy tools. With Okera, data users can use data responsibly, while protecting them from inappropriately accessing data that is confidential, personally identifiable, or regulated. Okera’s robust audit capabilities and data usage intelligence deliver the real-time and historical information that data security, compliance, and data delivery teams need to respond quickly to incidents, optimize processes, and analyze the performance of enterprise data initiatives.

Apache Sentry™ serves as a robust system for implementing detailed role-based authorization for both data and metadata within a Hadoop cluster environment. Achieving Top-Level Apache project status after graduating from the Incubator in March 2016, Apache Sentry is recognized for its effectiveness in managing granular authorization. It empowers users and applications to have precise control over access privileges to data stored in Hadoop, ensuring that only authenticated entities can interact with sensitive information. Compatibility extends to a range of frameworks, including Apache Hive, Hive Metastore/HCatalog, Apache Solr, Impala, and HDFS, though its primary focus is on Hive table data. Designed as a flexible and pluggable authorization engine, Sentry allows for the creation of tailored authorization rules that assess and validate access requests for various Hadoop resources. Its modular architecture increases its adaptability, making it capable of supporting a diverse array of data models within the Hadoop ecosystem. This flexibility positions Sentry as a vital tool for organizations aiming to manage their data security effectively.

Bigtop is a project under the Apache Foundation designed for Infrastructure Engineers and Data Scientists who need a thorough solution for packaging, testing, and configuring leading open source big data technologies. It encompasses a variety of components and projects, such as Hadoop, HBase, and Spark, among others. By packaging Hadoop RPMs and DEBs, Bigtop simplifies the management and maintenance of Hadoop clusters. Additionally, it offers an integrated smoke testing framework, complete with a collection of over 50 test files to ensure reliability. For those looking to deploy Hadoop from scratch, Bigtop provides vagrant recipes, raw images, and in-progress docker recipes. The framework is compatible with numerous Operating Systems, including Debian, Ubuntu, CentOS, Fedora, and openSUSE, among others. Moreover, Bigtop incorporates a comprehensive set of tools and a testing framework that evaluates various aspects, such as packaging, platform, and runtime, which are essential for both new deployments and upgrades of the entire data platform, rather than just isolated components. This makes Bigtop a vital resource for anyone aiming to streamline their big data infrastructure.

Secuvy, a next-generation cloud platform, automates data security, privacy compliance, and governance via AI-driven workflows. Unstructured data is treated with the best data intelligence. Secuvy, a next-generation cloud platform that automates data security, privacy compliance, and governance via AI-driven workflows is called Secuvy. Unstructured data is treated with the best data intelligence. Automated data discovery, customizable subjects access requests, user validations and data maps & workflows to comply with privacy regulations such as the ccpa or gdpr. Data intelligence is used to locate sensitive and private information in multiple data stores, both in motion and at rest. Our mission is to assist organizations in protecting their brand, automating processes, and improving customer trust in a world that is rapidly changing. We want to reduce human effort, costs and errors in handling sensitive data.

IntraFind's iFinder offers a comprehensive search solution that serves as a hub for all of your organization’s data. This platform seamlessly connects to various data sources within your enterprise. As your data repositories expand, iFinder prepares you for the future: leveraging Elasticsearch technology, it can effortlessly scale to accommodate any data volume. By utilizing artificial intelligence, it enhances search outcomes, providing intelligent enterprise search capabilities. Whether your essential documents and information reside on company drives, intranet pages, wikis, or email systems, iFinder streamlines the process of locating them. Embrace the next phase of your organization's digital evolution by centralizing access to all data through our innovative enterprise search solution. By implementing iFinder, you're not just enhancing search efficiency; you're also optimizing how your team interacts with information.

Excelero offers a low-latency distributed block storage solution tailored for web-scale applications. With NVMesh, users can access shared NVMe technology over any network while maintaining compatibility with both local and distributed file systems. The platform includes a sophisticated management layer that abstracts the underlying hardware, supports CPU offload, and facilitates the creation of logical volumes with built-in redundancy, all while providing centralized management and monitoring capabilities. This allows applications to leverage the speed, throughput, and IOPS of local NVMe devices combined with the benefits of centralized storage, all without being tied to proprietary hardware, ultimately lowering the total cost of ownership for storage. Additionally, NVMesh's distributed block layer empowers unmodified applications to tap into pooled NVMe storage resources, achieving performance levels comparable to local access. Moreover, users can dynamically create arbitrary block volumes that can be accessed by any host equipped with the NVMesh block client, enhancing flexibility and scalability in storage deployments. This innovative approach not only optimizes resource utilization but also simplifies management across diverse infrastructures.

lakeFS allows you to control your data lake similarly to how you manage your source code, facilitating parallel pipelines for experimentation as well as continuous integration and deployment for your data. This platform streamlines the workflows of engineers, data scientists, and analysts who are driving innovation through data. As an open-source solution, lakeFS enhances the resilience and manageability of object-storage-based data lakes. With lakeFS, you can execute reliable, atomic, and versioned operations on your data lake, encompassing everything from intricate ETL processes to advanced data science and analytics tasks. It is compatible with major cloud storage options, including AWS S3, Azure Blob Storage, and Google Cloud Storage (GCS). Furthermore, lakeFS seamlessly integrates with a variety of modern data frameworks such as Spark, Hive, AWS Athena, and Presto, thanks to its API compatibility with S3. The platform features a Git-like model for branching and committing that can efficiently scale to handle exabytes of data while leveraging the storage capabilities of S3, GCS, or Azure Blob. In addition, lakeFS empowers teams to collaborate more effectively by allowing multiple users to work on the same dataset without conflicts, making it an invaluable tool for data-driven organizations.

Prodea enables the rapid launch of secure, scalable, and globally compliant connected products and services within a six-month timeframe. As the sole provider of an IoT platform-as-a-service (PaaS) tailored for manufacturers of mass-market consumer home products, Prodea offers three core services: the IoT Service X-Change Platform, which allows for the swift introduction of connected products into diverse global markets with minimal development effort; Insight™ Data Services, which provides critical insights derived from user and product usage analytics; and the EcoAdaptor™ Service, designed to enhance the value of products through seamless cloud-to-cloud integration and interoperability with various other products and services. Prodea has successfully assisted its global brand partners in launching over 100 connected products, averaging less than six months for completion, across six continents. This achievement is largely attributed to the Prodea X5 Program, which integrates with the three primary cloud services to support brands in evolving their systems effectively and efficiently. Additionally, this comprehensive approach ensures that manufacturers can adapt to changing market demands while maximizing their connectivity capabilities.

GO+ provides development resources tailored for service providers, enabling them to create additional offerings for their business clientele. The platform is designed to handle a large volume of devices simultaneously through advanced algorithms. This allows service providers to focus less on the challenges of developing new services for their customers. At the heart of the platform lies an analytical decision-making engine that utilizes Granular Computing for intricate data processing and analysis with complex event handling. We leverage cloud technology that seamlessly integrates business logic from real devices directly to the cloud environment. This scalability ensures that we can offer cost-effective solutions. Additionally, the platform's scripting engine equips developers with a comprehensive suite of tools to craft highly customized IoT services applicable across various industries. GO+ is constructed on cutting-edge cloud computing technology, ensuring optimal performance and reliability. Ultimately, GO+ empowers service providers to innovate without the typical constraints associated with service development.

Foghub streamlines the integration of IT and OT, enhancing data engineering and real-time intelligence at the edge. Its user-friendly, cross-platform design employs an open architecture to efficiently manage industrial time-series data. By facilitating the critical link between operational components like sensors, devices, and systems, and business elements such as personnel, processes, and applications, Foghub enables seamless automated data collection and engineering processes, including transformations, advanced analytics, and machine learning. The platform adeptly manages a diverse range of industrial data types, accommodating significant variety, volume, and velocity, while supporting a wide array of industrial network protocols, OT systems, and databases. Users can effortlessly automate data gathering related to production runs, batches, parts, cycle times, process parameters, asset health, utilities, consumables, and operator performance. Built with scalability in mind, Foghub provides an extensive suite of features to efficiently process and analyze large amounts of data, ensuring that businesses can maintain optimal performance and decision-making capabilities. As industries evolve and data demands increase, Foghub remains a pivotal solution for achieving effective IT/OT convergence.

Brainwave is transforming how you evaluate user access! With an innovative user interface, enhanced predictive controls, and comprehensive risk-scoring features, you can now conduct in-depth access risk analyses. The Autonomous Identity solution allows your teams to operate more effectively with a user-friendly, industry-recognized tool that speeds up your identity management initiatives (IGA). This empowers organizations to assess and make informed decisions regarding access to shared files and folders. You can inventory, categorize, review access, and ensure compliance irrespective of the environment, whether it be file servers, NAS, Sharepoint, Office 365, and beyond. Our flagship offering, Brainwave Identity GRC, is packed with analytical tools that make the most of your access inventory. Enjoy constant visibility across all resources at any given moment. Furthermore, Brainwave’s extensive inventory serves as an entitlement catalog that spans across various infrastructure, business applications, and data access points, ensuring a comprehensive overview of user permissions. This holistic approach promotes better security and informed decision-making.

Apache Kylin™ is a distributed, open-source Analytical Data Warehouse designed for Big Data, aimed at delivering OLAP (Online Analytical Processing) capabilities in the modern big data landscape. By enhancing multi-dimensional cube technology and precalculation methods on platforms like Hadoop and Spark, Kylin maintains a consistent query performance, even as data volumes continue to expand. This innovation reduces query response times from several minutes to just milliseconds, effectively reintroducing online analytics into the realm of big data. Capable of processing over 10 billion rows in under a second, Kylin eliminates the delays previously associated with report generation, facilitating timely decision-making. It seamlessly integrates data stored on Hadoop with popular BI tools such as Tableau, PowerBI/Excel, MSTR, QlikSense, Hue, and SuperSet, significantly accelerating business intelligence operations on Hadoop. As a robust Analytical Data Warehouse, Kylin supports ANSI SQL queries on Hadoop/Spark and encompasses a wide array of ANSI SQL functions. Moreover, Kylin’s architecture allows it to handle thousands of simultaneous interactive queries with minimal resource usage, ensuring efficient analytics even under heavy loads. This efficiency positions Kylin as an essential tool for organizations seeking to leverage their data for strategic insights.

A web-based notebook facilitates interactive data analytics and collaborative documentation using SQL, Scala, and other languages. With an IPython interpreter, it delivers a user experience similar to that of Jupyter Notebook. The latest version introduces several enhancements, including a dynamic form at the note level, a note revision comparison tool, and the option to execute paragraphs sequentially rather than simultaneously, as was the case in earlier versions. Additionally, an interpreter lifecycle manager ensures that idle interpreter processes are automatically terminated, freeing up resources when they are not actively being utilized. This improvement not only optimizes performance but also enhances the overall user experience.

SOLIXCloud CDP provides a cloud-based data management solution tailored for contemporary data-centric businesses. Utilizing open-source and cloud-native technologies, it enables organizations to effectively handle and analyze their structured, semi-structured, and unstructured data, facilitating advanced analytics, regulatory compliance, infrastructure efficiency, and robust data security. Key components of this platform include Solix Connect for efficient data ingestion, Solix Data Governance, Solix Metadata Management, and Solix Search, collectively forming a holistic framework for managing cloud data. This framework supports the development and operation of data-driven applications, including SQL data warehouses, machine learning models, and artificial intelligence systems, while addressing the increasing complexities associated with data management regulations, data retention policies, and consumer privacy concerns. In this way, SOLIXCloud CDP empowers companies to navigate the evolving landscape of data management with confidence.

The volume of data continues to increase, yet not all data carries the same significance. Companies that embrace cloud data management can effectively lower their enterprise data management expenses while ensuring security, compliance, high performance, and straightforward accessibility. As time passes, the value of content diminishes; however, organizations can still generate revenue from older data using innovative SaaS-based solutions. SOLIXCloud provides all the necessary features to achieve an ideal equilibrium between managing both historical and current data. In addition to its robust compliance functionalities for structured, unstructured, and semi-structured data, SOLIXCloud presents a comprehensive managed service for all types of enterprise data. Furthermore, Solix's metadata management framework serves as a complete solution for analyzing all enterprise metadata and lineage from a single, centralized repository, supported by a comprehensive business glossary that enhances organizational efficiency. This holistic approach allows businesses to derive insights from their data, regardless of its age.

Utilizing graph analytics throughout the customer lifecycle can help uncover hidden risks and unveil unexpected opportunities. Conventional Master Data Management (MDM) solutions struggle to accommodate the vast amounts of distributed and diverse data generated from various applications and external sources. The traditional methods of probabilistic matching in MDM are ineffective when dealing with siloed data sources, leading to missed connections and a lack of context, ultimately resulting in poor decision-making and uncapitalized business value. An inadequate MDM solution can have widespread repercussions, negatively impacting both the customer experience and operational efficiency. When there's no immediate access to comprehensive payment patterns, trends, and risks, your team’s ability to make informed decisions swiftly is compromised, compliance expenses increase, and expanding coverage becomes a challenge. If your data remains unintegrated, it creates fragmented customer experiences across different channels, business sectors, and regions. Efforts to engage customers on a personal level often fail, as they rely on incomplete and frequently outdated information, highlighting the urgent need for a more cohesive approach to data management. This lack of a unified data strategy not only hampers customer satisfaction but also stifles business growth opportunities.

Witboost is an adaptable, high-speed, and effective data management solution designed to help businesses fully embrace a data-driven approach while cutting down on time-to-market, IT spending, and operational costs. The system consists of various modules, each serving as a functional building block that can operate independently to tackle specific challenges or be integrated to form a comprehensive data management framework tailored to your organization’s requirements. These individual modules enhance particular data engineering processes, allowing for a seamless combination that ensures swift implementation and significantly minimizes time-to-market and time-to-value, thereby lowering the overall cost of ownership of your data infrastructure. As urban environments evolve, smart cities increasingly rely on digital twins to forecast needs and mitigate potential issues, leveraging data from countless sources and managing increasingly intricate telematics systems. This approach not only facilitates better decision-making but also ensures that cities can adapt efficiently to ever-changing demands.

Enhance your understanding of documents and make informed decisions with assurance. Are you weary of the challenges posed by manual processing, tight deadlines, budget constraints, and constantly evolving compliance regulations? Effortlessly collect and integrate your cloud expenditure data in half the time and at a fraction of the cost. With suggested cost reductions and expert advice, you could potentially save over 50% on your total expenses. Achieve comprehensive visibility of your cloud spending through KPI monitoring, real-time analytics, and actionable recommendations. Experience built-in reassurance with security and compliance measures designed to adhere to any regulatory standards. You can gather data through various channels, including portals, emails, APIs, repositories, tables, data lakes, or third-party sources. The automated AI-driven intelligent document processing minimizes manual workload, while the smart review of document knowledge detects anomalies, duplicates, and mistakes. Utilize ScriptString's Knowledge Relationship Indexing to effortlessly pinpoint critical information amidst vast data sets. This innovative approach not only streamlines your processes but also transforms the way you manage your cloud spending.

The Occubee platform seamlessly transforms vast quantities of receipt information, encompassing thousands of products along with numerous retail-specific metrics, into actionable sales and demand predictions. At the retail level, Occubee delivers precise sales forecasts for each product and initiates restocking requests. In warehouse settings, it enhances product availability and capital allocation while also generating supplier orders. Furthermore, at the corporate office, Occubee offers continuous oversight of sales activities, issuing alerts for any anomalies and producing comprehensive reports. The innovative technologies employed for data gathering and processing facilitate the automation of crucial business operations within the retail sector. By addressing the evolving requirements of contemporary retail, Occubee aligns perfectly with global megatrends that emphasize data utilization in business strategies. This comprehensive approach not only streamlines operations but also empowers retailers to make informed decisions that enhance overall efficiency.

Acxiom provides the tools necessary to utilize extensive data for understanding premium audiences and gaining insights worldwide. By effectively engaging and personalizing experiences both online and offline, brands can better comprehend, identify, and target their ideal customers. In this “borderless digital world” where marketing technology, identity resolution, and digital connectivity intersect, organizations can swiftly uncover data attributes, service availability, and digital footprints globally, enabling them to make well-informed decisions. As a global leader in data, Acxiom offers thousands of data attributes across over 60 countries, assisting brands in enhancing millions of customer experiences daily through valuable, data-driven insights while prioritizing consumer privacy. With Acxiom, brands can grasp, connect with, and engage diverse audiences, optimize their media investments, and create more tailored experiences. Ultimately, Acxiom empowers brands to reach global audiences effectively and deliver impactful experiences that resonate.

DL4J leverages state-of-the-art distributed computing frameworks like Apache Spark and Hadoop to enhance the speed of training processes. When utilized with multiple GPUs, its performance matches that of Caffe. Fully open-source under the Apache 2.0 license, the libraries are actively maintained by both the developer community and the Konduit team. Deeplearning4j, which is developed in Java, is compatible with any language that runs on the JVM, including Scala, Clojure, and Kotlin. The core computations are executed using C, C++, and CUDA, while Keras is designated as the Python API. Eclipse Deeplearning4j stands out as the pioneering commercial-grade, open-source, distributed deep-learning library tailored for Java and Scala applications. By integrating with Hadoop and Apache Spark, DL4J effectively introduces artificial intelligence capabilities to business settings, enabling operations on distributed CPUs and GPUs. Training a deep-learning network involves tuning numerous parameters, and we have made efforts to clarify these settings, allowing Deeplearning4j to function as a versatile DIY resource for developers using Java, Scala, Clojure, and Kotlin. With its robust framework, DL4J not only simplifies the deep learning process but also fosters innovation in machine learning across various industries.

Span Global Services stands as a leader in the realm of digital and data-centric marketing solutions. We infuse every campaign with precise insights that drive B2B sales and marketing outcomes across a wide array of sectors, including technology, healthcare, manufacturing, retail, and telecommunications, among others. With access to over 90 million rigorously verified contacts, along with comprehensive business firmographics and entity relationships, our tailored databases meet the data needs of both large corporations and small to medium enterprises. Our methodology for acquiring and validating data combines advanced technology, public records, and direct human interactions, ensuring a personal touch in our outreach. Clients focusing on sales and marketing experience enhanced MQL and conversion rates, coupled with guaranteed data quality and bespoke appending and profiling solutions. Furthermore, we provide marketing automation services and leverage the industry’s top subject matter expertise, ensuring our clients stay ahead in a competitive market landscape. Through our commitment to excellence, we empower businesses to navigate their marketing strategies with confidence and precision.

A Kudu cluster comprises tables that resemble those found in traditional relational (SQL) databases. These tables can range from a straightforward binary key and value structure to intricate designs featuring hundreds of strongly-typed attributes. Similar to SQL tables, each Kudu table is defined by a primary key, which consists of one or more columns; this could be a single unique user identifier or a composite key such as a (host, metric, timestamp) combination tailored for time-series data from machines. The primary key allows for quick reading, updating, or deletion of rows. The straightforward data model of Kudu facilitates the migration of legacy applications as well as the development of new ones, eliminating concerns about encoding data into binary formats or navigating through cumbersome JSON databases. Additionally, tables in Kudu are self-describing, enabling the use of standard analysis tools like SQL engines or Spark. With user-friendly APIs, Kudu ensures that developers can easily integrate and manipulate their data. This approach not only streamlines data management but also enhances overall efficiency in data processing tasks.

Parquet was developed to provide the benefits of efficient, compressed columnar data representation to all projects within the Hadoop ecosystem. Designed with a focus on accommodating complex nested data structures, Parquet employs the record shredding and assembly technique outlined in the Dremel paper, which we consider to be a more effective strategy than merely flattening nested namespaces. This format supports highly efficient compression and encoding methods, and various projects have shown the significant performance improvements that arise from utilizing appropriate compression and encoding strategies for their datasets. Furthermore, Parquet enables the specification of compression schemes at the column level, ensuring its adaptability for future developments in encoding technologies. It is crafted to be accessible for any user, as the Hadoop ecosystem comprises a diverse range of data processing frameworks, and we aim to remain neutral in our support for these different initiatives. Ultimately, our goal is to empower users with a flexible and robust tool that enhances their data management capabilities across various applications.

Hypertable provides a high-performance, scalable database solution that enhances the efficiency of your big data applications while minimizing hardware usage. This platform offers exceptional efficiency and outperforms its competitors, leading to significant cost reductions for users. Its robust and proven architecture supports numerous services at Google. Users can enjoy the advantages of open-source technology backed by a vibrant and active community. With a C++ implementation, Hypertable ensures optimal performance. Additionally, it offers around-the-clock support for critical big data operations. Clients benefit from direct access to the expertise of the core developers behind Hypertable. Specifically engineered to address scalability challenges that traditional relational database management systems struggle with, Hypertable leverages a design model pioneered by Google to effectively tackle scaling issues, making it superior to other NoSQL alternatives available today. Its innovative approach not only resolves current scalability needs but also anticipates future demands in data management.

Pinot is built to efficiently handle OLAP queries on static data with minimal latency. It incorporates various pluggable indexing methods, including Sorted Index, Bitmap Index, and Inverted Index. While it currently lacks support for joins, this limitation can be mitigated by utilizing Trino or PrestoDB for querying purposes. The system offers an SQL-like language that enables selection, aggregation, filtering, grouping, ordering, and distinct queries on datasets. It comprises both offline and real-time tables, with real-time tables being utilized to address segments lacking offline data. Additionally, users can tailor the anomaly detection process and notification mechanisms to accurately identify anomalies. This flexibility ensures that users can maintain data integrity and respond proactively to potential issues.

Hudi serves as a robust platform for constructing streaming data lakes equipped with incremental data pipelines, all while utilizing a self-managing database layer that is finely tuned for lake engines and conventional batch processing. It effectively keeps a timeline of every action taken on the table at various moments, enabling immediate views of the data while also facilitating the efficient retrieval of records in the order they were received. Each Hudi instant is composed of several essential components, allowing for streamlined operations. The platform excels in performing efficient upserts by consistently linking a specific hoodie key to a corresponding file ID through an indexing system. This relationship between record key and file group or file ID remains constant once the initial version of a record is written to a file, ensuring stability in data management. Consequently, the designated file group encompasses all iterations of a collection of records, allowing for seamless data versioning and retrieval. This design enhances both the reliability and efficiency of data operations within the Hudi ecosystem.

Utilize widely-used open-source frameworks like Apache Hadoop, Spark, Hive, and Kafka with Azure HDInsight, a customizable and enterprise-level service designed for open-source analytics. Effortlessly manage vast data sets while leveraging the extensive open-source project ecosystem alongside Azure’s global capabilities. Transitioning your big data workloads to the cloud is straightforward and efficient. You can swiftly deploy open-source projects and clusters without the hassle of hardware installation or infrastructure management. The big data clusters are designed to minimize expenses through features like autoscaling and pricing tiers that let you pay solely for your actual usage. With industry-leading security and compliance validated by over 30 certifications, your data is well protected. Additionally, Azure HDInsight ensures you remain current with the optimized components tailored for technologies such as Hadoop and Spark, providing an efficient and reliable solution for your analytics needs. This service not only streamlines processes but also enhances collaboration across teams.

Harness the capabilities of both private and public clouds through a unique hybrid data platform tailored for contemporary data architectures, enabling data access from any location. Cloudera stands out as a hybrid data platform that offers unparalleled flexibility, allowing users to choose any cloud, any analytics solution, and any type of data. It streamlines data management and analytics, ensuring optimal performance, scalability, and security for data accessibility from anywhere. By leveraging Cloudera, organizations can benefit from the strengths of both private and public clouds, leading to quicker value realization and enhanced control over IT resources. Moreover, Cloudera empowers users to securely transfer data, applications, and individuals in both directions between their data center and various cloud environments, irrespective of the data's physical location. This bi-directional capability not only enhances operational efficiency but also fosters a more adaptable and responsive data strategy.

At Datametica, our innovative solutions significantly reduce risks and alleviate costs, time, frustration, and anxiety throughout the data warehouse migration process to the cloud. We facilitate the transition of your current data warehouse, data lake, ETL, and enterprise business intelligence systems to your preferred cloud environment through our automated product suite. Our approach involves crafting a comprehensive migration strategy that includes workload discovery, assessment, planning, and cloud optimization. With our Eagle tool, we provide insights from the initial discovery and assessment phases of your existing data warehouse to the development of a tailored migration strategy, detailing what data needs to be moved, the optimal sequence for migration, and the anticipated timelines and expenses. This thorough overview of workloads and planning not only minimizes migration risks but also ensures that business operations remain unaffected during the transition. Furthermore, our commitment to a seamless migration process helps organizations embrace cloud technologies with confidence and clarity.

A comprehensive incident and emergency management system designed for routine operations as well as crisis scenarios. This command, control, and communication (C3) framework leverages advanced data analytics alongside social and mobile technologies to enhance the coordination and integration of preparation, response, recovery, and mitigation efforts for everyday incidents, emergencies, and disasters. IBM collaborates with government agencies and public safety organizations across the globe to deploy innovative public safety technology solutions. Effective preparation strategies utilize the same tools to address routine community incidents, enabling a seamless transition to crisis response. This established familiarity allows first responders and C3 personnel to engage swiftly and intuitively in various phases of response, recovery, and mitigation without relying on specialized documentation or systems. Furthermore, this incident and emergency management solution synthesizes and aligns multiple information sources, creating a dynamic, near real-time geospatial framework that supports a unified operational view for all stakeholders involved. By doing so, it enhances situational awareness and fosters more efficient communication during critical events.

Red Hat JBoss Data Virtualization serves as an efficient solution for virtual data integration, effectively releasing data that is otherwise inaccessible and presenting it in a unified, user-friendly format that can be easily acted upon. It allows data from various, physically distinct sources, such as different databases, XML files, and Hadoop systems, to be viewed as a cohesive set of tables within a local database. This solution provides real-time, standards-based read and write access to a variety of heterogeneous data repositories. By streamlining the process of accessing distributed data, it accelerates both application development and integration. Users can integrate and adapt data semantics to meet the specific requirements of data consumers. Additionally, it offers central management for access control and robust auditing processes through a comprehensive security framework. As a result, fragmented data can be transformed into valuable insights swiftly, catering to the dynamic needs of businesses. Moreover, Red Hat provides ongoing support and maintenance for its JBoss products during specified periods, ensuring that users have access to the latest enhancements and assistance.

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.

IBM InfoSphere® Optim™ Data Privacy offers a comprehensive suite of tools designed to effectively mask sensitive information in non-production settings like development, testing, quality assurance, or training. This singular solution employs various transformation methods to replace sensitive data with realistic, fully functional masked alternatives, ensuring the confidentiality of critical information. Techniques for masking include using substrings, arithmetic expressions, generating random or sequential numbers, manipulating dates, and concatenating data elements. The advanced masking capabilities maintain contextually appropriate formats that closely resemble the original data. Users can apply an array of masking techniques on demand to safeguard personally identifiable information and sensitive corporate data within applications, databases, and reports. By utilizing these data masking features, organizations can mitigate the risk of data misuse by obscuring, privatizing, and protecting personal information circulated in non-production environments, thereby enhancing data security and compliance. Ultimately, this solution empowers businesses to navigate privacy challenges while maintaining the integrity of their operational processes.

Driving the most efficient, compact, scalable, and adaptable storage solution in existence, the Pavilion HyperParallel File System™ enables unlimited scalability across numerous Pavilion HyperParallel Flash Arrays™, achieving an impressive 1.2 TB/s for read operations and 900 GB/s for writes, alongside 200 million IOPS at a mere 25 microseconds latency for each rack. This system stands out with its remarkable ability to offer independent and linear scalability for both capacity and performance, as the Pavilion HyperOS 3 now incorporates global namespace support for NFS and S3, thus facilitating boundless, linear scaling across countless Pavilion HyperParallel Flash Array units. By harnessing the capabilities of the Pavilion HyperParallel Flash Array, users can experience unmatched levels of performance and uptime. Furthermore, the Pavilion HyperOS integrates innovative, patent-pending technologies that guarantee constant data availability, providing swift access that far surpasses traditional legacy arrays. This combination of scalability and performance positions Pavilion as a leader in the storage industry, catering to the needs of modern data-driven environments.

Invenis serves as a robust platform for data analysis and mining, enabling users to easily clean, aggregate, and analyze their data while scaling efforts to enhance decision-making processes. It offers capabilities such as data harmonization, preparation, cleansing, enrichment, and aggregation, alongside powerful predictive analytics, segmentation, and recommendation features. By connecting seamlessly to various data sources like MySQL, Oracle, Postgres SQL, and HDFS (Hadoop), Invenis facilitates comprehensive analysis of diverse file formats, including CSV and JSON. Users can generate predictions across all datasets without requiring coding skills or a specialized team of experts, as the platform intelligently selects the most suitable algorithms based on the specific data and use cases presented. Additionally, Invenis automates repetitive tasks and recurring analyses, allowing users to save valuable time and fully leverage the potential of their data. Collaboration is also enhanced, as teams can work together, not only among analysts but across various departments, streamlining decision-making processes and ensuring that information flows efficiently throughout the organization. This collaborative approach ultimately empowers businesses to make better-informed decisions based on timely and accurate data insights.

Integration Eye® is a versatile modular solution designed to optimize system integrations, infrastructure, and business operations. It comprises three distinct modules: the proxy module IPM, the logging module ILM, and the security module ISM, each of which can function independently or work in unison. Built on the secure and widely adopted Java programming language, it operates efficiently on the lightweight integration engine Mule™. With the individual modules of Integration Eye®, users can effectively monitor their APIs and systems, generate statistics, and analyze API calls through the ILM module, while also receiving alerts for any issues like downtime or slow responses from specific APIs and systems. Additionally, the ISM module allows you to enhance security for your APIs and systems through role-based access control, leveraging either the Keycloak SSO we provide or your existing authentication server. The IPM module further enables the extension or proxying of service calls, both internal and external, with features like mutual SSL and customizable headers, while also allowing for the monitoring and analysis of these communications. This comprehensive approach ensures that your business operations are not only streamlined but also secure and resilient against potential disruptions.

A framework for distributed data integration that streamlines essential functions of Big Data integration, including data ingestion, replication, organization, and lifecycle management, is designed for both streaming and batch data environments. It operates as a standalone application on a single machine and can also function in an embedded mode. Additionally, it is capable of executing as a MapReduce application across various Hadoop versions and offers compatibility with Azkaban for initiating MapReduce jobs. In standalone cluster mode, it features primary and worker nodes, providing high availability and the flexibility to run on bare metal systems. Furthermore, it can function as an elastic cluster in the public cloud, maintaining high availability in this setup. Currently, Gobblin serves as a versatile framework for creating various data integration applications, such as ingestion and replication. Each application is usually set up as an independent job and managed through a scheduler like Azkaban, allowing for organized execution and management of data workflows. This adaptability makes Gobblin an appealing choice for organizations looking to enhance their data integration processes.

Unify Your Data Stack: Experience the first no-code data pipeline platform and power enlightened decision making. Integrate.io is the only complete set of data solutions & connectors for easy building and managing of clean, secure data pipelines. Increase your data team's output with all of the simple, powerful tools & connectors you’ll ever need in one no-code data integration platform. Empower any size team to consistently deliver projects on-time & under budget. Integrate.io's Platform includes: -No-Code ETL & Reverse ETL: Drag & drop no-code data pipelines with 220+ out-of-the-box data transformations -Easy ELT & CDC :The Fastest Data Replication On The Market -Automated API Generation: Build Automated, Secure APIs in Minutes - Data Warehouse Monitoring: Finally Understand Your Warehouse Spend - FREE Data Observability: Custom Pipeline Alerts to Monitor Data in Real-Time