Alternatives to SHREWD Platform

Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.

We are excited to introduce a groundbreaking big data platform designed for the music industry, which consolidates all relevant information into a single, reliable source to inform strategic decisions. Within the music business sector, numerous data sources exist, but they are often isolated and disjointed. Our innovative platform effectively identifies and integrates these sources, establishing a robust foundation of high-quality data applicable to everyday operations in the music industry. To operate effectively and securely while uncovering unique insights, record labels and agencies need an advanced data management and governance framework that ensures data is consistently accessible, pertinent, and practical. As data sources are integrated into Wavo’s Big Data Platform, machine learning techniques are utilized to categorize the data according to customized templates, facilitating easy access and deep dives into crucial information. This capability empowers every member of a music organization to harness and utilize data that is prepared and organized for immediate application and value creation. Ultimately, our platform serves as a catalyst for smarter decision-making and enhanced operational efficiency across the music business landscape.

Gartner's Magic Quadrant includes Centralpoint as a Digital Experience Platform. It is used by more than 350 clients around the world, and it goes beyond Enterprise Content Management. It securely authenticates (AD/SAML/OpenID, oAuth), all users for self-service interaction. Centralpoint automatically aggregates information from different sources and applies rich metadata against your rules to produce true Knowledge Management. This allows you to search for and relate disparate data sets from anywhere. Centralpoint's Module Gallery is the most robust and can be installed either on-premise or in the cloud. Check out our solutions for Automating Metadata and Automating Retention Policy Management. We also offer solutions to simplify the mashup of disparate data to benefit from AI (Artificial Intelligence). Centralpoint is often used to provide easy migration tools and an intelligent alternative to Sharepoint. It can be used to secure portal solutions for public sites, intranets, members, or extranets.

Cazena's Instant Data Lake significantly reduces the time needed for analytics and AI/ML from several months to just a few minutes. Utilizing its unique automated data platform, Cazena introduces a pioneering SaaS model for data lakes, requiring no operational input from users. Businesses today seek a data lake that can seamlessly accommodate all their data and essential tools for analytics, machine learning, and artificial intelligence. For a data lake to be truly effective, it must ensure secure data ingestion, provide adaptable data storage, manage access and identities, facilitate integration with various tools, and optimize performance among other features. Building cloud data lakes independently can be quite complex and typically necessitates costly specialized teams. Cazena's Instant Cloud Data Lakes are not only designed to be readily operational for data loading and analytics but also come with a fully automated setup. Supported by Cazena’s SaaS Platform, they offer ongoing operational support and self-service access through the user-friendly Cazena SaaS Console. With Cazena's Instant Data Lakes, users have a completely turnkey solution that is primed for secure data ingestion, efficient storage, and comprehensive analytics capabilities, making it an invaluable resource for enterprises looking to harness their data effectively and swiftly.

5X is a comprehensive data management platform that consolidates all the necessary tools for centralizing, cleaning, modeling, and analyzing your data. With its user-friendly design, 5X seamlessly integrates with more than 500 data sources, allowing for smooth and continuous data flow across various systems through both pre-built and custom connectors. The platform features a wide array of functions, including ingestion, data warehousing, modeling, orchestration, and business intelligence, all presented within an intuitive interface. It efficiently manages diverse data movements from SaaS applications, databases, ERPs, and files, ensuring that data is automatically and securely transferred to data warehouses and lakes. Security is a top priority for 5X, as it encrypts data at the source and identifies personally identifiable information, applying encryption at the column level to safeguard sensitive data. Additionally, the platform is engineered to lower the total cost of ownership by 30% when compared to developing a custom solution, thereby boosting productivity through a single interface that enables the construction of complete data pipelines from start to finish. This makes 5X an ideal choice for businesses aiming to streamline their data processes effectively.

Delta Lake serves as an open-source storage layer that integrates ACID transactions into Apache Spark™ and big data operations. In typical data lakes, multiple pipelines operate simultaneously to read and write data, which often forces data engineers to engage in a complex and time-consuming effort to maintain data integrity because transactional capabilities are absent. By incorporating ACID transactions, Delta Lake enhances data lakes and ensures a high level of consistency with its serializability feature, the most robust isolation level available. For further insights, refer to Diving into Delta Lake: Unpacking the Transaction Log. In the realm of big data, even metadata can reach substantial sizes, and Delta Lake manages metadata with the same significance as the actual data, utilizing Spark's distributed processing strengths for efficient handling. Consequently, Delta Lake is capable of managing massive tables that can scale to petabytes, containing billions of partitions and files without difficulty. Additionally, Delta Lake offers data snapshots, which allow developers to retrieve and revert to previous data versions, facilitating audits, rollbacks, or the replication of experiments while ensuring data reliability and consistency across the board.

Optimize your time and reduce expenses by simplifying data pipelines using hassle-free open source solutions. Covering everything from data ingestion to visualization, all components are seamlessly integrated, fully managed, and exceptionally reliable, ensuring your engineering team enjoys working with data. You can opt for any of DoubleCloud’s managed open source services or take advantage of the entire platform's capabilities, which include data storage, orchestration, ELT, and instantaneous visualization. We offer premier open source services such as ClickHouse, Kafka, and Airflow, deployable on platforms like Amazon Web Services or Google Cloud. Our no-code ELT tool enables real-time data synchronization between various systems, providing a fast, serverless solution that integrates effortlessly with your existing setup. With our managed open-source data visualization tools, you can easily create real-time visual representations of your data through interactive charts and dashboards. Ultimately, our platform is crafted to enhance the daily operations of engineers, making their tasks more efficient and enjoyable. This focus on convenience is what sets us apart in the industry.

Hopsworks is a comprehensive open-source platform designed to facilitate the creation and management of scalable Machine Learning (ML) pipelines, featuring the industry's pioneering Feature Store for ML. Users can effortlessly transition from data analysis and model creation in Python, utilizing Jupyter notebooks and conda, to executing robust, production-ready ML pipelines without needing to acquire knowledge about managing a Kubernetes cluster. The platform is capable of ingesting data from a variety of sources, whether they reside in the cloud, on-premise, within IoT networks, or stem from your Industry 4.0 initiatives. You have the flexibility to deploy Hopsworks either on your own infrastructure or via your chosen cloud provider, ensuring a consistent user experience regardless of the deployment environment, be it in the cloud or a highly secure air-gapped setup. Moreover, Hopsworks allows you to customize alerts for various events triggered throughout the ingestion process, enhancing your workflow efficiency. This makes it an ideal choice for teams looking to streamline their ML operations while maintaining control over their data environments.

DataLux is an innovative platform designed for effective data management and analytics, specifically created to tackle various data-related issues while facilitating real-time decision-making. Equipped with user-friendly plug-and-play adaptors, it enables the aggregation of extensive data collections and offers the capability to collect and visualize insights instantaneously. Utilize the data lake to anticipate and drive new innovations, while ensuring that data is stored in a manner conducive to modeling. The platform allows for the development of portable applications by leveraging containerization, whether in a public cloud, private cloud, or on-premise environment. It seamlessly integrates diverse time-series market data and inferred information, including stock exchange tick data, market policy actions, relevant cross-industry news, and alternative datasets, to derive causal insights regarding stock markets and macroeconomic factors. By providing valuable insights, DataLux empowers businesses to shape their decisions and foster product innovations effectively. Additionally, it supports interdisciplinary A/B testing throughout the product development lifecycle, from initial ideation to final decision-making, ensuring a comprehensive approach to enhancing design and engineering processes.

Strategizing, innovating, and advancing. From identification of needs to implementation of solutions. Introducing the eDrain DATA CLOUD PLATFORM. This platform is designed specifically for the collection, monitoring, and generation of comprehensive reports on data. It functions within the realm of Big Data, utilizing a driver-centric approach that facilitates the integration of various types of data. The advanced driver engine allows for the simultaneous incorporation of numerous data streams and devices. Its features include the ability to customize dashboards, add different views, and create tailored widgets, along with configuring new devices, flows, and sensors. Users can also set up custom reports, monitor sensor statuses, and manage real-time data flows. Additionally, it enables the definition of flow logic, analysis rules, and warning thresholds, as well as configuration for events and actions. New devices can be created and new stations configured, allowing for the effective management and verification of alerts, ensuring a comprehensive data management experience. This platform empowers users to take full control of their data environment.

Smart DIH is a data management platform that quickly serves applications with accurate, fresh and complete data, delivering high performance, ultra-low latency, and an always-on digital experience. Smart DIH decouples APIs from SoRs, replicating critical data, and making it available using event-driven architecture. Smart DIH enables drastically shorter development cycles of new digital services, and rapidly scales to serve millions of concurrent users – no matter which IT infrastructure or cloud topologies it relies on. XAP Skyline is a distributed in-memory development platform that delivers transactional consistency, combined with extreme event-based processing and microsecond latency. The platform fuels core business solutions that rely on instantaneous data, including online trading, real-time risk management and data processing for AI and large language models.

Sadas Engine is the fastest columnar database management system in cloud and on-premise. Sadas Engine is the solution that you are looking for. * Store * Manage * Analyze It takes a lot of data to find the right solution. * BI * DWH * Data Analytics The fastest columnar Database Management System can turn data into information. It is 100 times faster than transactional DBMSs, and can perform searches on large amounts of data for a period that lasts longer than 10 years.

CENX Service Assurance offers a comprehensive view of service topology, inventory, faults, and performance across various systems, bringing them together into one cohesive interface. This level of insight empowers operators to enhance hybrid communication networks and implement automated processes effectively. Consequently, they can rapidly roll out next-generation services, explore innovative business models, and embrace advanced technologies like Network Functions Virtualization (NFV), Software-Defined Networking (SDN), Self-organizing Networks (SON), as well as 5G and IoT, all while keeping costs manageable. By fundamentally transforming how service providers interact with their networks, CENX Service Assurance delivers nearly real-time actionable visibility, triggers closed-loop actions, and integrates inventory and fault correlation, supplemented by Threshold Crossover Alert (TCA) analysis on performance metrics from various sources. This innovative approach paves the way for numerous cutting-edge enterprise applications within the realm of 5G technology, pushing the boundaries of what is possible in network management.

BryteFlow creates remarkably efficient automated analytics environments that redefine data processing. By transforming Amazon S3 into a powerful analytics platform, it skillfully utilizes the AWS ecosystem to provide rapid data delivery. It works seamlessly alongside AWS Lake Formation and automates the Modern Data Architecture, enhancing both performance and productivity. Users can achieve full automation in data ingestion effortlessly through BryteFlow Ingest’s intuitive point-and-click interface, while BryteFlow XL Ingest is particularly effective for the initial ingestion of very large datasets, all without the need for any coding. Moreover, BryteFlow Blend allows users to integrate and transform data from diverse sources such as Oracle, SQL Server, Salesforce, and SAP, preparing it for advanced analytics and machine learning applications. With BryteFlow TruData, the reconciliation process between the source and destination data occurs continuously or at a user-defined frequency, ensuring data integrity. If any discrepancies or missing information arise, users receive timely alerts, enabling them to address issues swiftly, thus maintaining a smooth data flow. This comprehensive suite of tools ensures that businesses can operate with confidence in their data's accuracy and accessibility.

Varada offers a cutting-edge big data indexing solution that adeptly balances performance and cost while eliminating the need for data operations. This distinct technology acts as an intelligent acceleration layer within your data lake, which remains the central source of truth and operates within the customer's cloud infrastructure (VPC). By empowering data teams to operationalize their entire data lake, Varada facilitates data democratization while ensuring fast, interactive performance, all without requiring data relocation, modeling, or manual optimization. The key advantage lies in Varada's capability to automatically and dynamically index pertinent data, maintaining the structure and granularity of the original source. Additionally, Varada ensures that any query can keep pace with the constantly changing performance and concurrency demands of users and analytics APIs, while also maintaining predictable cost management. The platform intelligently determines which queries to accelerate and which datasets to index, while also flexibly adjusting the cluster to match demand, thereby optimizing both performance and expenses. This holistic approach to data management not only enhances operational efficiency but also allows organizations to remain agile in an ever-evolving data landscape.

An AI-driven self-service platform for advanced analytics allows users to connect diverse data sources and create visualizations effortlessly, eliminating the need for programming skills. This cloud-native solution delivers high-quality data and intelligent real-time insights across the organization with a no-code approach. Users can link various data sources, regardless of their formats, enabling the detection of underlying issues. The platform significantly reduces the time taken from sourcing to targeting data, while providing analytics accessible to those without technical expertise. With real-time data updates, users can connect any kind of data source, streaming it to a data lake at defined intervals, and visualize the information through sophisticated interactive dashboards. It combines descriptive, predictive, and prescriptive analytics in one platform, utilizing the capabilities of a search engine alongside advanced visualization techniques. There’s no need for conventional technology to explore data in multiple visualization styles. Users can easily manipulate data through roll-ups, slicing, and dicing, employing various mathematical computations directly within the Bizintel360 visualization environment, thus enhancing their analytical capabilities. This empowers businesses to make data-driven decisions with ease and speed.

Qubole stands out as a straightforward, accessible, and secure Data Lake Platform tailored for machine learning, streaming, and ad-hoc analysis. Our comprehensive platform streamlines the execution of Data pipelines, Streaming Analytics, and Machine Learning tasks across any cloud environment, significantly minimizing both time and effort. No other solution matches the openness and versatility in handling data workloads that Qubole provides, all while achieving a reduction in cloud data lake expenses by more than 50 percent. By enabling quicker access to extensive petabytes of secure, reliable, and trustworthy datasets, we empower users to work with both structured and unstructured data for Analytics and Machine Learning purposes. Users can efficiently perform ETL processes, analytics, and AI/ML tasks in a seamless workflow, utilizing top-tier open-source engines along with a variety of formats, libraries, and programming languages tailored to their data's volume, diversity, service level agreements (SLAs), and organizational regulations. This adaptability ensures that Qubole remains a preferred choice for organizations aiming to optimize their data management strategies while leveraging the latest technological advancements.

BIRD Analytics is an exceptionally rapid, high-performance, comprehensive platform for data management and analytics that leverages agile business intelligence alongside AI and machine learning models to extract valuable insights. It encompasses every component of the data lifecycle, including ingestion, transformation, wrangling, modeling, and real-time analysis, all capable of handling petabyte-scale datasets. With self-service features akin to Google search and robust ChatBot integration, BIRD empowers users to find solutions quickly. Our curated resources deliver insights, from industry use cases to informative blog posts, illustrating how BIRD effectively tackles challenges associated with Big Data. After recognizing the advantages BIRD offers, you can arrange a demo to witness the platform's capabilities firsthand and explore how it can revolutionize your specific data requirements. By harnessing AI and machine learning technologies, organizations can enhance their agility and responsiveness in decision-making, achieve cost savings, and elevate customer experiences significantly. Ultimately, BIRD Analytics positions itself as an essential tool for businesses aiming to thrive in a data-driven landscape.

Introducing a comprehensive Big Data Platform designed to enhance intelligence and streamline efficiency for your organization, equipped with tools that make the data journey more accessible. Develop algorithms, harness Artificial Intelligence, leverage Machine Learning, and much more to propel your business forward. With this platform, you can consolidate every aspect of your data-driven journey from start to finish, effectively centralizing information and fostering data-driven insights. Experience seamless ingestion, engineering, scientific analysis, and data visualization all in one cohesive process. The technology is robust, ready for operations, and agnostic, simplifying data governance while ensuring versatility. Furthermore, the user-friendly Marketplace interface offers pre-built algorithms and the ability to extend functionalities through APIs. This platform stands as the singular solution to centralize and unify the entirety of your business's data journey, setting a new standard for operational excellence and insight generation. Embrace the future of data management with a platform that adapts to your unique business needs.

Apache Druid is a distributed data storage solution that is open source. Its fundamental architecture merges concepts from data warehouses, time series databases, and search technologies to deliver a high-performance analytics database capable of handling a diverse array of applications. By integrating the essential features from these three types of systems, Druid optimizes its ingestion process, storage method, querying capabilities, and overall structure. Each column is stored and compressed separately, allowing the system to access only the relevant columns for a specific query, which enhances speed for scans, rankings, and groupings. Additionally, Druid constructs inverted indexes for string data to facilitate rapid searching and filtering. It also includes pre-built connectors for various platforms such as Apache Kafka, HDFS, and AWS S3, as well as stream processors and others. The system adeptly partitions data over time, making queries based on time significantly quicker than those in conventional databases. Users can easily scale resources by simply adding or removing servers, and Druid will manage the rebalancing automatically. Furthermore, its fault-tolerant design ensures resilience by effectively navigating around any server malfunctions that may occur. This combination of features makes Druid a robust choice for organizations seeking efficient and reliable real-time data analytics solutions.

Unlike most data management systems, PHEMI Health DataLab is built with Privacy-by-Design principles, not as an add-on. This means privacy and data governance are built-in from the ground up, providing you with distinct advantages: Lets analysts work with data without breaching privacy guidelines Includes a comprehensive, extensible library of de-identification algorithms to hide, mask, truncate, group, and anonymize data. Creates dataset-specific or system-wide pseudonyms enabling linking and sharing of data without risking data leakage. Collects audit logs concerning not only what changes were made to the PHEMI system, but also data access patterns. Automatically generates human and machine-readable de- identification reports to meet your enterprise governance risk and compliance guidelines. Rather than a policy per data access point, PHEMI gives you the advantage of one central policy for all access patterns, whether Spark, ODBC, REST, export, and more

Currently, less than 10% of the vast $260 billion big data industry is being utilized, primarily due to outdated processes and the overpowering presence of intermediaries. Our goal is to democratize this market, enabling access to the remaining 90% of data that is currently untapped for sharing. We aim to establish a decentralized framework that creates a data oracle network, utilizing an open protocol that facilitates interaction among participants while fostering a sustainable economy. Our multifunctional decentralized application (DAPP) and crypto wallet provide users with the opportunity to earn rewards for the data they generate, alongside access to various decentralized finance (DeFi) tools through a seamless user experience. The GeoDB marketplace empowers data buyers globally to acquire data produced by users through applications linked to the GeoDB platform. Participants, known as data sources, contribute data that is uploaded via our proprietary and partner applications, while validators ensure the efficient transfer and verification of contracts through blockchain technology, allowing for a streamlined and decentralized process. This innovative approach not only enhances data accessibility but also promotes a collaborative environment for all stakeholders involved.

Paxata is an innovative, user-friendly platform that allows business analysts to quickly ingest, analyze, and transform various raw datasets into useful information independently, significantly speeding up the process of generating actionable business insights. Besides supporting business analysts and subject matter experts, Paxata offers an extensive suite of automation tools and data preparation features that can be integrated into other applications to streamline data preparation as a service. The Paxata Adaptive Information Platform (AIP) brings together data integration, quality assurance, semantic enhancement, collaboration, and robust data governance, all while maintaining transparent data lineage through self-documentation. Utilizing a highly flexible multi-tenant cloud architecture, Paxata AIP stands out as the only contemporary information platform that operates as a multi-cloud hybrid information fabric, ensuring versatility and scalability in data handling. This unique approach not only enhances efficiency but also fosters collaboration across different teams within an organization.

Mindtree's Decision Moments stands out as the pioneering data analytics platform that harnesses continuous learning algorithms to analyze extensive datasets. This groundbreaking sense-and-respond mechanism enables organizations to reveal valuable insights that evolve over time, thereby enhancing the value derived from their digital transformation efforts. As an agile and adaptable data intelligence platform, Decision Moments effectively alleviates technological complexities by seamlessly aligning with your organization’s pre-existing data analytics investments. Furthermore, it possesses the necessary flexibility to adjust in accordance with fluctuations in market conditions, technological advancements, or varying business requirements. To maximize the benefits and cost efficiencies associated with a data analytics platform, Decision Moments leverages Microsoft Azure services, including the Cortana Intelligence Suite, within a cloud-native framework. Ultimately, Mindtree’s Decision Moments equips your key decision-makers with the essential tools to interpret vast amounts of data sourced from diverse origins, ensuring they can make informed choices in a rapidly evolving landscape. This robust platform not only aids in immediate decision-making but also fosters a culture of continuous improvement within organizations.

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.

Begin your top-down evaluation with a comprehensive view of a sample Data Platform, allowing you to navigate through different areas and uncover their connections to various organizational data. From the transformation of a supply chain's business model to the implementation of Enterprise Data Platform strategies in a banking institution, there are numerous real-world examples demonstrating the effectiveness of Indyco as a data modeling tool. This initiative significantly bolstered the data culture within a prominent player in the food and agriculture sector in Italy, ultimately facilitating the advent of self-service reporting. Business users began engaging with the Conceptual Model displayed on a large screen, collaborating with IT teams during co-design sessions focused on refining their Data Platform. Additionally, a bank successfully established best practices for Data Platform design by utilizing Indyco, which included elements such as conceptual modeling, automated documentation, and the creation of a business glossary. Thus, the integration of these practices not only streamlined processes but also fostered an environment where data-driven decision-making could thrive.

Mosaic is a Strategic Finance Platform for agile planning, real-time reporting, deep analysis, and more accurate forecasting. Easily consolidating data from ERP, CRM, HRIS, and Billing systems, the platform provides a single-source-of-truth across the business, aligning teams and enabling better decision-making. Today, Mosaic's software is deployed by some of the fastest-growing companies, helping them manage current business performance and plan for the future.

For more four decades, IRI CoSort has defined the state-of-the-art in big data sorting and transformation technology. From advanced algorithms to automatic memory management, and from multi-core exploitation to I/O optimization, there is no more proven performer for production data processing than CoSort. CoSort was the first commercial sort package developed for open systems: CP/M in 1980, MS-DOS in 1982, Unix in 1985, and Windows in 1995. Repeatedly reported to be the fastest commercial-grade sort product for Unix. CoSort was also judged by PC Week to be the "top performing" sort on Windows. CoSort was released for CP/M in 1978, DOS in 1980, Unix in the mid-eighties, and Windows in the early nineties, and received a readership award from DM Review magazine in 2000. CoSort was first designed as a file sorting utility, and added interfaces to replace or convert sort program parameters used in IBM DataStage, Informatica, MF COBOL, JCL, NATURAL, SAS, and SyncSort. In 1992, CoSort added related manipulation functions through a control language interface based on VMS sort utility syntax, which evolved through the years to handle structured data integration and staging for flat files and RDBs, and multiple spinoff products.

DataWorks, a comprehensive Big Data platform introduced by Alibaba Cloud, offers an all-in-one solution for Big Data development, management of data permissions, offline job scheduling, and more. The platform is designed to function seamlessly right from the start, eliminating the need for users to manage complex underlying clusters and operations. Users can effortlessly build workflows through a drag-and-drop interface, while also having the ability to edit and debug their code in real-time, inviting collaboration from fellow developers. The platform supports a wide range of functionalities, including data integration, MaxCompute SQL, MaxCompute MR, machine learning, and shell tasks. Additionally, it features robust task monitoring capabilities, providing alerts in case of errors to prevent service disruptions. With the ability to run millions of tasks simultaneously, DataWorks accommodates various scheduling options, including hourly, daily, weekly, and monthly tasks. As an exceptional platform for constructing big data warehouses, DataWorks delivers extensive data warehousing services, catering to all aspects of data aggregation, processing, governance, and services. Its user-friendly design and powerful features make it an indispensable tool for organizations looking to harness the power of Big Data effectively.

Amazon EMR stands as the leading cloud-based big data solution for handling extensive datasets through popular open-source frameworks like Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. This platform enables you to conduct Petabyte-scale analyses at a cost that is less than half of traditional on-premises systems and delivers performance more than three times faster than typical Apache Spark operations. For short-duration tasks, you have the flexibility to quickly launch and terminate clusters, incurring charges only for the seconds the instances are active. In contrast, for extended workloads, you can establish highly available clusters that automatically adapt to fluctuating demand. Additionally, if you already utilize open-source technologies like Apache Spark and Apache Hive on-premises, you can seamlessly operate EMR clusters on AWS Outposts. Furthermore, you can leverage open-source machine learning libraries such as Apache Spark MLlib, TensorFlow, and Apache MXNet for data analysis. Integrating with Amazon SageMaker Studio allows for efficient large-scale model training, comprehensive analysis, and detailed reporting, enhancing your data processing capabilities even further. This robust infrastructure is ideal for organizations seeking to maximize efficiency while minimizing costs in their data operations.

Gravwell is an all you can ingest data fusion platform that allows for complete context and root cause analysis for security and business data. Gravwell was created to provide machine data benefits to all customers, large or small, binary or text, security or operational. An analytics platform that can do things you've never seen before is possible when experienced hackers team up with big data experts. Gravwell provides security analytics that go beyond log data to industrial processes, vehicle fleets, IT infrastructure or all of it. Do you need to track down an access breach? Gravwell can run facial recognition machine-learning against camera data to identify multiple subjects who enter a facility with one badge-in. Gravwell can also correlate building access logs. We are here to help people who require more than text log searching and want it sooner than they can afford.

EMR serves as a comprehensive enterprise-grade big data platform, offering cluster, job, and data management functionalities that leverage various open-source technologies, including Hadoop, Spark, Kafka, Flink, and Storm. Alibaba Cloud Elastic MapReduce (EMR) is specifically designed for big data processing within the Alibaba Cloud ecosystem. Built on Alibaba Cloud's ECS instances, EMR integrates the capabilities of open-source Apache Hadoop and Apache Spark. This platform enables users to utilize components from the Hadoop and Spark ecosystems, such as Apache Hive, Apache Kafka, Flink, Druid, and TensorFlow, for effective data analysis and processing. Users can seamlessly process data stored across multiple Alibaba Cloud storage solutions, including Object Storage Service (OSS), Log Service (SLS), and Relational Database Service (RDS). EMR also simplifies cluster creation, allowing users to establish clusters rapidly without the hassle of hardware and software configuration. Additionally, all maintenance tasks can be managed efficiently through its user-friendly web interface, making it accessible for various users regardless of their technical expertise.

We offer a user-friendly Data Access Automation Platform designed to generate tailored data sets and derivative applications such as search engines and data dashboards, making it easier to understand and utilize data effectively. Our innovative solutions empower organizations to retrieve the information they require in a manner that suits their needs, ultimately enhancing performance and helping them reach their business objectives. Utilizing advanced crawlers and connectors, we explore websites, cloud services of your choosing, and internal systems to gather the essential information and data dictated by your specific business rules. This capability allows for seamless reintegration into your existing internal data systems, thereby improving the effectiveness of data exploitation. With our platform, you can not only access vital insights but also leverage them to drive strategic decisions and foster growth.

DataMax is an enterprise-ready solution that simplifies the intricate aspects of real-time data management, enabling organizations to develop, deploy, and operate at scale with ease. This platform enhances the speed at which businesses can implement change. Featuring a distinctive architecture, process, and a blend of specialized technologies, DataMax transitions organizations from scattered data and reporting sources to a comprehensive data overview, granting them the insights necessary for more efficient operations. Its innovative combination of technologies ensures robust data management suitable for enterprise demands. The system has demonstrated its scalability and is designed for cloud deployment, accommodating both time series and non-time series data. By generating analytics platforms, it significantly elevates the quality of data, analysis, and reporting available to market analytics teams, thereby enhancing the decision-making capabilities of Traders. Ultimately, DataMax empowers organizations to respond swiftly to market dynamics and improve their overall business strategies.

Using a user-friendly spreadsheet platform, field representatives, payer marketers, partners, brand marketers, pricing and reimbursement specialists, and managed market professionals can input data into a permission-based system that aggregates information for headquarters. This data can be shared through UQ subscription reports or various third-party reporting tools, allowing you to effortlessly generate necessary reports with just a few clicks. You can set priorities for key performance indicators, identify essential metrics, and channel information into diverse reporting frameworks. Additionally, safeguard sensitive information with user-specific access controls during both the data collection and distribution phases. Address any workflow inconsistencies that arise between standard spreadsheets and comprehensive enterprise solutions. Moreover, facilitate the interconnection, harmonization, and synchronization of data across different systems to enhance overall efficiency and accuracy. This streamlined approach not only improves collaboration but also ensures that all stakeholders have access to the most relevant and up-to-date information.

Apache Arrow establishes a columnar memory format that is independent of any programming language, designed to handle both flat and hierarchical data, which allows for optimized analytical processes on contemporary hardware such as CPUs and GPUs. This memory format enables zero-copy reads, facilitating rapid data access without incurring serialization delays. Libraries associated with Arrow not only adhere to this format but also serve as foundational tools for diverse applications, particularly in high-performance analytics. Numerous well-known projects leverage Arrow to efficiently manage columnar data or utilize it as a foundation for analytic frameworks. Developed by the community for the community, Apache Arrow emphasizes open communication and collaborative decision-making. With contributors from various organizations and backgrounds, we encourage inclusive participation in our ongoing efforts and developments. Through collective contributions, we aim to enhance the functionality and accessibility of data analytics tools.

ROBIN is the first hyper-converged Kubernetes platform in the industry for big data, databases and AI/ML. The platform offers a self-service App store experience to deploy any application anywhere. It runs on-premises in your private cloud or in public-cloud environments (AWS, Azure and GCP). Hyper-converged Kubernetes combines containerized storage and networking with compute (Kubernetes) and the application management layer to create a single system. Our approach extends Kubernetes to data-intensive applications like Hortonworks, Cloudera and Elastic stack, RDBMSs, NoSQL database, and AI/ML. Facilitates faster and easier roll-out of important Enterprise IT and LoB initiatives such as containerization and cloud-migration, cost consolidation, productivity improvement, and cost-consolidation. This solution addresses the fundamental problems of managing big data and databases in Kubernetes.

Seerene’s Digital Engineering Platform offers advanced software analytics and process mining capabilities that scrutinize and visualize your company’s software development workflows. By identifying inefficiencies, this platform transforms your organization into a streamlined entity, enabling software delivery that is not only efficient and cost-effective but also rapid and of superior quality. It equips leaders with the insights necessary to steer their teams towards achieving comprehensive software excellence. The platform can uncover code segments that are prone to defects, adversely affecting developer efficiency, and identify high-performing teams, allowing their exemplary processes to be adopted organization-wide. Additionally, it highlights potential defect risks in release candidates through a thorough examination of code, development hotspots, and testing methodologies. It also brings to light features where there is a discrepancy between the time invested by developers and the value delivered to users, as well as code that remains unused by end-users, which incurs unnecessary maintenance expenditure. Ultimately, Seerene empowers organizations to optimize their software development lifecycle and enhance overall productivity.

A platform for Machine Learning and Predictive Analytics enhances data-driven decision-making and propels business growth through sophisticated artificial intelligence within an integrated machine learning and big data analytics framework. OpenText Magellan leverages AI technologies to deliver predictive analytics through user-friendly and adaptable data visualizations that enhance the utility of business intelligence. The implementation of artificial intelligence software streamlines the big data processing task, providing essential business insights in a format that aligns with the organization’s most significant goals. By enriching business operations with a tailored combination of features such as predictive modeling, data exploration tools, data mining methods, and IoT data analytics, companies can effectively utilize their data to refine their decision-making processes based on actionable business intelligence and analytics. This comprehensive approach not only improves operational efficiency but also fosters a culture of data-driven innovation within the organization.

Panoply makes it easy to store, sync and access all your business information in the cloud. With built-in integrations to all major CRMs and file systems, building a single source of truth for your data has never been easier. Panoply is quick to set up and requires no ongoing maintenance. It also offers award-winning support, and a plan to fit any need.

Address the complexities of value-based care regardless of your existing EHR system. Gain a comprehensive understanding of your patient demographics through consolidated data from various sources, presented in an intuitive visual format. Leverage data-driven insights to enhance the management of chronic diseases and facilitate smoother transitions in care, while also working to prevent illnesses, reduce costs, and enhance care management initiatives. Promote effective care coordination through tools designed for a proactive mindset, including a pre-visit dashboard, risk assessment capabilities, and automated monitoring of admission, discharge, and transfer activities. Activate care management strategies to broaden the reach of healthcare providers. Encourage essential patient interactions and ensure meaningful follow-up between visits. Utilize the Johns Hopkins ACG system for risk stratification to pinpoint patients most at risk for high-cost healthcare utilization. Efficiently allocate resources to areas where they are most urgently needed. Aim to elevate performance metrics related to quality care. Engage successfully in value-based payment initiatives and maximize reimbursement opportunities as you navigate this evolving landscape. By implementing these strategies, healthcare organizations can improve patient outcomes and foster a more sustainable care environment.

Lentiq offers a collaborative data lake as a service that empowers small teams to achieve significant results. It allows users to swiftly execute data science, machine learning, and data analysis within the cloud platform of their choice. With Lentiq, teams can seamlessly ingest data in real time, process and clean it, and share their findings effortlessly. This platform also facilitates the building, training, and internal sharing of models, enabling data teams to collaborate freely and innovate without limitations. Data lakes serve as versatile storage and processing environments, equipped with machine learning, ETL, and schema-on-read querying features, among others. If you’re delving into the realm of data science, a data lake is essential for your success. In today’s landscape, characterized by the Post-Hadoop era, large centralized data lakes have become outdated. Instead, Lentiq introduces data pools—interconnected mini-data lakes across multiple clouds—that work harmoniously to provide a secure, stable, and efficient environment for data science endeavors. This innovative approach enhances the overall agility and effectiveness of data-driven projects.

Tamr offers a cutting-edge data mastering platform that combines machine learning and human input to eliminate data silos, ensuring continuous data cleansing and accurate information flow throughout your organization. Collaborating with top companies globally, Tamr addresses significant data-related challenges they face. Resolve issues such as duplicate entries and inaccuracies to gain a comprehensive understanding of your data, encompassing everything from customers to products and suppliers. This advanced data mastering solution not only streamlines the integration of machine learning and human expertise but also facilitates delivering reliable data that informs business decisions effectively. By providing clean data to analytics and operational systems, it reduces the effort required by up to 80% compared to conventional methods. Tamr empowers financial institutions to maintain a data-driven approach and enhance their business results, while also assisting public sector organizations in achieving their mission goals faster by minimizing manual processes associated with data entity resolution. Ultimately, Tamr’s platform fosters a more efficient data landscape, driving innovation and improved decision-making across various sectors.

EntelliFusion by Teksouth is a fully managed, end to end solution. EntelliFusion's architecture is a one-stop solution for outfitting a company's data infrastructure. Instead of trying to put together multiple platforms for data prep, data warehouse and governance, and then deploying a lot of IT resources to make it all work, EntelliFusion's architecture offers a single platform. EntelliFusion unites data silos into a single platform that allows for cross-functional KPI's. This creates powerful insights and holistic solutions. EntelliFusion's "military born" technology has been able to withstand the rigorous demands of the USA's top echelon in military operations. It was scaled up across the DOD over twenty years. EntelliFusion is built using the most recent Microsoft technologies and frameworks, which allows it to continue being improved and innovated. EntelliFusion is data-agnostic and infinitely scalable. It guarantees accuracy and performance to encourage end-user tool adoption.

SmartHub Analytics is a specialized platform for telecom big-data analytics that focuses on financial and subscriber-centric ROI-driven applications. It is specifically developed to foster data sharing and reuse, thereby enhancing business performance and providing analytics that are instantly actionable. By breaking down silos, SmartHub Analytics can evaluate, verify, and model extensive datasets from TEOCO’s array of solutions, which encompass areas like customer management, planning, optimization, service assurance, geo-location, service quality, and costs. Additionally, as an extra analytics layer integrated with existing OSS and BSS systems, SmartHub Analytics establishes an independent analytics environment that has demonstrated substantial returns on investment, allowing operators to save billions. Our approach frequently reveals substantial cost reductions for clients through the application of predictive machine learning techniques. Moreover, SmartHub Analytics consistently leads the industry by offering rapid data analysis capabilities, ensuring that businesses can adapt and respond to market changes with agility and precision.