Latest news with #StewartBond
Channel Post MEA
6 days ago
- Business
- Channel Post MEA
Confluent Announces New Cloud Capabilities For Data Streaming
Confluent has announced new Confluent Cloud capabilities that make it easier to process and secure data for faster insights and decision-making. Snapshot queries, new in Confluent Cloud for Apache Flink, bring together real-time and historic data processing to make artificial intelligence (AI) agents and analytics smarter. Confluent Cloud network (CCN) routing simplifies private networking for Apache Flink, and IP Filtering adds access controls for publicly accessible Flink pipelines, securing data for agentic AI and analytics. 'Agentic AI is moving from hype to enterprise adoption as organizations look to gain a competitive edge and win in today's market,' said Shaun Clowes, Chief Product Officer at Confluent. 'But without high-quality data, even the most advanced systems can't deliver real value. The new Confluent Cloud for Apache Flink features make it possible to blend real-time and batch data so that enterprises can trust their agentic AI to drive real change.' Bridging the Real-Time and Batch Divide 'The rise of agentic AI orchestration is expected to accelerate, and companies need to start preparing now,' said Stewart Bond, Vice President of Data Intelligence and Integration Software at IDC. 'To unlock agentic AI's full potential, companies should seek solutions that unify disparate data types, including structured, unstructured, real-time, and historical information, in a single environment. This allows AI to derive richer insights and drive more impactful outcomes.' Agentic AI is driving widespread change in business operations by increasing efficiency and powering faster decision-making by analyzing data to uncover valuable trends and insights. However, for AI agents to make the right decisions, they need historical context about what happened in the past and insight into what's happening right now. For example, for fraud detection, banks need real-time data to react in the moment and historical data to see if a transaction fits a customer's usual patterns. Hospitals need real-time vitals alongside patient medical history to make safe, informed treatment decisions. But to leverage both past and present data, teams often have to use separate tools and develop manual workarounds, resulting in time-consuming work and broken workflows. Additionally, it's important to secure the data that's used for analytics and agentic AI; this ensures trustworthy results and prevents sensitive data from being accessed. Snapshot Queries Unify Processing on One Platform In Confluent Cloud, snapshot queries let teams unify historical and streaming data with a single product and language, enabling consistent, intelligent experiences for both analytics and agentic AI. With seamless Tableflow integration, teams can easily gain context from past data. Snapshot queries allow teams to explore, test, and analyze data without spinning up new workloads. This makes it easier to supply agents with context from historic and real-time data or conduct an audit to understand key trends and patterns. Snapshot queries are now available in early access. CCN Routing Simplifies Private Networking for Flink Private networking is important for organizations that require an additional layer of security. Confluent offers a streamlined private networking solution by reusing existing CCNs that teams have already created for Apache Kafka clusters. Teams can use CCN to securely connect their data to any Flink workload, such as streaming pipelines, AI agents, or analytics. CCN routing is now generally available on Amazon Web Services (AWS) in all regions where Flink is supported. IP Filtering Protects Flink Workloads in Hybrid Environments Many organizations that operate in hybrid environments need more control over which data can be publicly accessed. IP Filtering for Flink helps teams restrict internet traffic to allowed IPs and improves visibility into unauthorized access attempts by making it easier to track the attempts. IP Filtering is generally available for all Confluent Cloud users. Now organizations can more easily turn the promise of agentic AI into a competitive advantage. To learn more about the other new Confluent Cloud features, including the Snowflake source connector, cross-cloud Cluster Linking, and new Schema Registry private networking features, check out the launch blog. 0 0
Mid East Info
03-06-2025
- Business
- Mid East Info
Confluent Unites Batch and Stream Processing for Faster, Smarter Agentic AI and Analytics - Middle East Business News and Information
Confluent, Inc. (Nasdaq: CFLT), the data streaming pioneer, announced new Confluent Cloud capabilities that make it easier to process and secure data for faster insights and decision-making. Snapshot queries, new in Confluent Cloud for Apache Flink®, bring together real-time and historic data processing to make artificial intelligence (AI) agents and analytics smarter. Confluent Cloud network (CCN) routing simplifies private networking for Apache Flink®, and IP Filtering adds access controls for publicly accessible Flink pipelines, securing data for agentic AI and analytics. 'Agentic AI is moving from hype to enterprise adoption as organizations look to gain a competitive edge and win in today's market,' said Shaun Clowes, Chief Product Officer at Confluent. 'But without high-quality data, even the most advanced systems can't deliver real value. The new Confluent Cloud for Apache Flink® features make it possible to blend real-time and batch data so that enterprises can trust their agentic AI to drive real change.' Bridging the Real-Time and Batch Divide 'The rise of agentic AI orchestration is expected to accelerate, and companies need to start preparing now,' said Stewart Bond, Vice President of Data Intelligence and Integration Software at IDC. 'To unlock agentic AI's full potential, companies should seek solutions that unify disparate data types, including structured, unstructured, real-time, and historical information, in a single environment. This allows AI to derive richer insights and drive more impactful outcomes.' Agentic AI is driving widespread change in business operations by increasing efficiency and powering faster decision-making by analyzing data to uncover valuable trends and insights. However, for AI agents to make the right decisions, they need historical context about what happened in the past and insight into what's happening right now. For example, for fraud detection, banks need real-time data to react in the moment and historical data to see if a transaction fits a customer's usual patterns. Hospitals need real-time vitals alongside patient medical history to make safe, informed treatment decisions. But to leverage both past and present data, teams often have to use separate tools and develop manual workarounds, resulting in time-consuming work and broken workflows. Additionally, it's important to secure the data that's used for analytics and agentic AI; this ensures trustworthy results and prevents sensitive data from being accessed. Snapshot Queries Unify Processing on One Platform In Confluent Cloud, snapshot queries let teams unify historical and streaming data with a single product and language, enabling consistent, intelligent experiences for both analytics and agentic AI. With seamless Tableflow integration, teams can easily gain context from past data. Snapshot queries allow teams to explore, test, and analyze data without spinning up new workloads. This makes it easier to supply agents with context from historic and real-time data or conduct an audit to understand key trends and patterns. Snapshot queries are now available in early access. CCN Routing Simplifies Private Networking for Flink Private networking is important for organizations that require an additional layer of security. Confluent offers a streamlined private networking solution by reusing existing CCNs that teams have already created for Apache Kafka® clusters. Teams can use CCN to securely connect their data to any Flink workload, such as streaming pipelines, AI agents, or analytics. CCN routing is now generally available on Amazon Web Services (AWS) in all regions where Flink is supported. IP Filtering Protects Flink Workloads in Hybrid Environments Many organizations that operate in hybrid environments need more control over which data can be publicly accessed. IP Filtering for Flink helps teams restrict internet traffic to allowed IPs and improves visibility into unauthorized access attempts by making it easier to track the attempts. IP Filtering is generally available for all Confluent Cloud users. Now organizations can more easily turn the promise of agentic AI into a competitive advantage. To learn more about the other new Confluent Cloud features, including the Snowflake source connector, cross-cloud Cluster Linking, and new Schema Registry private networking features, check out the launch blog.
Business Wire
20-05-2025
- Business
- Business Wire
Confluent Unites Batch and Stream Processing for Faster, Smarter Agentic AI and Analytics
LONDON--(BUSINESS WIRE)-- Confluent, Inc. (Nasdaq: CFLT), the data streaming pioneer, announced new Confluent Cloud capabilities that make it easier to process and secure data for faster insights and decision-making. Snapshot queries, new in Confluent Cloud for Apache Flink ®, bring together real-time and historic data processing to make artificial intelligence (AI) agents and analytics smarter. Confluent Cloud network (CCN) routing simplifies private networking for Apache Flink ®, and IP Filtering adds access controls for publicly accessible Flink pipelines, securing data for agentic AI and analytics. 'Agentic AI is moving from hype to enterprise adoption as organizations look to gain a competitive edge and win in today's market,' said Shaun Clowes, Chief Product Officer at Confluent. 'But without high-quality data, even the most advanced systems can't deliver real value. The new Confluent Cloud for Apache Flink ® features make it possible to blend real-time and batch data so that enterprises can trust their agentic AI to drive real change.' Bridging the Real-Time and Batch Divide 'The rise of agentic AI orchestration is expected to accelerate, and companies need to start preparing now,' said Stewart Bond, Vice President of Data Intelligence and Integration Software at IDC. 'To unlock agentic AI's full potential, companies should seek solutions that unify disparate data types, including structured, unstructured, real-time, and historical information, in a single environment. This allows AI to derive richer insights and drive more impactful outcomes.' Agentic AI is driving widespread change in business operations by increasing efficiency and powering faster decision-making by analyzing data to uncover valuable trends and insights. However, for AI agents to make the right decisions, they need historical context about what happened in the past and insight into what's happening right now. For example, for fraud detection, banks need real-time data to react in the moment and historical data to see if a transaction fits a customer's usual patterns. Hospitals need real-time vitals alongside patient medical history to make safe, informed treatment decisions. But to leverage both past and present data, teams often have to use separate tools and develop manual workarounds, resulting in time-consuming work and broken workflows. Additionally, it's important to secure the data that's used for analytics and agentic AI; this ensures trustworthy results and prevents sensitive data from being accessed. Snapshot Queries Unify Processing on One Platform In Confluent Cloud, snapshot queries let teams unify historical and streaming data with a single product and language, enabling consistent, intelligent experiences for both analytics and agentic AI. With seamless Tableflow integration, teams can easily gain context from past data. Snapshot queries allow teams to explore, test, and analyze data without spinning up new workloads. This makes it easier to supply agents with context from historic and real-time data or conduct an audit to understand key trends and patterns. Snapshot queries are now available in early access. CCN Routing Simplifies Private Networking for Flink Private networking is important for organizations that require an additional layer of security. Confluent offers a streamlined private networking solution by reusing existing CCNs that teams have already created for Apache Kafka ® clusters. Teams can use CCN to securely connect their data to any Flink workload, such as streaming pipelines, AI agents, or analytics. CCN routing is now generally available on Amazon Web Services (AWS) in all regions where Flink is supported. IP Filtering Protects Flink Workloads in Hybrid Environments Many organizations that operate in hybrid environments need more control over which data can be publicly accessed. IP Filtering for Flink helps teams restrict internet traffic to allowed IPs and improves visibility into unauthorized access attempts by making it easier to track the attempts. IP Filtering is generally available for all Confluent Cloud users. Now organizations can more easily turn the promise of agentic AI into a competitive advantage. To learn more about the other new Confluent Cloud features, including the Snowflake source connector, cross-cloud Cluster Linking, and new Schema Registry private networking features, check out the launch blog. Additional Resources Start your free trial of Confluent Cloud. No credit card required. Ask our Professional Services experts for faster adoption. Check out the launch blog about additional Confluent Cloud features. About Confluent Confluent is the data streaming platform that is pioneering a fundamentally new category of data infrastructure that sets data in motion. Confluent's cloud-native offering is the foundational platform for data in motion—designed to be the intelligent connective tissue enabling real-time data from multiple sources to constantly stream across an organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital frontend customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit As our roadmap may change in the future, the features referred to here may change, may not be delivered on time, or may not be delivered at all. This information is not a commitment to deliver any functionality, and customers should make their purchasing decisions based on features that are currently available. Confluent ® and associated marks are trademarks or registered trademarks of Confluent, Inc. Apache ®, Apache Kafka ®, Kafka ®, Apache Flink ®, and Flink ® are registered trademarks of the Apache Software Foundation in the United States and/or other countries. No endorsement by the Apache Software Foundation is implied by the use of these marks. All other trademarks are the property of their respective owners.
Yahoo
14-05-2025
- Business
- Yahoo
Quest Unveils AI Governance Solution Designed to Build Enterprise Data Trust
New Release Offers Automated AI Model Certification, Role-Based Data Experience, and GenAI-based Stewardship Tools in Preview AUSTIN, Texas, May 14, 2025 (GLOBE NEWSWIRE) -- Quest Software, a global leader in protecting critical IT assets, powering data for AI and analytics, and modernizing Microsoft and database platforms, today announced erwin Data Intelligence 15 - a major update to its AI governance platform. The new version gives organizations the tools to build trust in their data by certifying AI models, improving discovery, and reducing the manual effort of data governance. The release comes at a time when organizations face growing pressure to ensure AI-driven decisions are transparent, explainable, and based on reliable data. Why it Matters Without strong governance and trustworthy data, AI projects often fail. Gartner predicts that 30% of Generative AI projects will be abandoned after proof of concept by end of 2025. This gap between plans and reality often comes down to foundational issues like data readiness. erwin Data Intelligence 15 addresses these issues with automated AI model certification, a personalized data discovery experience, and new GenAI tools to accelerate governance tasks. 'As companies work to put AI into production, they face one critical question: Is our data good enough to trust the outcome?' said Bharath Vasudevan, Vice President of Product at Quest Software. 'This release helps companies confidently answer 'yes'. We provide the tools to certify AI models, quickly surface the most valuable data, and spend less time managing.' Quest's automated approach to AI model certification is already gaining industry attention for its ability to significantly improve AI readiness and trust. 'Automated AI model certification in erwin Data Intelligence 15 offers organizations greater visibility into the readiness and reliability of AI models and their supporting data,' said Stewart Bond, VP of Data Intelligence and Integration Software at IDC. 'This centralized approach to AI governance can help organizations advance their AI data readiness initiatives, supporting more successful AI outcomes while addressing regulatory and operational risks.' What's New in erwin Data Intelligence 15 AI Model Certification Certify AI models using Quest's structured seven-step framework—built into erwin Data Intelligence 15 -- as the only solution that automates AI model certification through data intelligence. It goes beyond basic tracking or compliance, guiding teams through a consistent process to move trusted models into production. Automatically track model maturity and data quality using a configurable certification framework. Classify AI models into customizable maturity tiers, with status visible to both governance and data science teams for centralized oversight. Data Valuation and Trust Scoring Score data using up to nine weighted criteria—including quality, relevance, usage, and governance completeness. Customize the weight of each based on business goals, and automatically generate a value score to highlight trusted, high-value assets. Assign gold, silver, or bronze tiering to make data value scores easy to recognize at a glance. Supports data monetization by making high-value data easier to discover and use. Role-Based Access to Marketplace Insights Persona-based landing pages in erwin Data Marketplace to accelerate discovery and governance of relevant assets. Choose from a library of ready-to-use visualizations for quick insights and filter results by asset type—such as data products, AI models, or business policies. Gain actionable insights on assets that are recently curated, highly scored, recommended, or require attention to improve the speed and efficiency of governance. Bonus for existing Microsoft Customers erwin Data Intelligence 15 includes a new erwin Standard Data Connector for Microsoft Dataverse. This allows organizations to ingest metadata from Dataverse, to gain visibility across their Microsoft data landscape while applying all of erwin's capabilities, including AI model certification, automated governance, trust scoring, and data marketplace integration. erwinAI - GenAI that lightens the load for Data Stewards Launching in preview alongside the erwin Data Intelligence 15 release, erwinAI is a GenAI-powered agentic chatbot that reduces manual governance with new data stewardship accelerators. This reduces manual effort and helps close governance gaps faster. Initial capabilities include: Speeding up the classification of tables and columns and tlp generation of business term definitions. Stewards can quickly spot missing classifications and incomplete definitions, then review, approve, and apply suggested updates—all through the agentic chatbot, with full audit trail support. Additional erwinAI capabilities will roll out throughout 2025, bringing new stewardship and discovery accelerators designed to make data governance smarter and more intuitive. How Quest Stands Apart Quest's erwin Data Intelligence provides automated, structured AI model certification and flexible, weighted data scoring, both based on governance best practices. Where others rely primarily on workflow tracking or usage analytics, erwin delivers comprehensive visibility into AI model readiness, data value, and governance status—in one platform. To explore all the features of erwin Data Intelligence 15 by Quest: Visit the erwin Data Intelligence page and watch the "What's New in erwin Data Intelligence 15" video: Register to attend the 'Introducing erwin Data Intelligence 15' webinar on June 4: Visit the erwin AI governance solutions page and watch the video to see how erwin supports AI governance: Watch the erwin Data Marketplace video to see the new user experience: About Quest SoftwareQuest creates software solutions that make the benefits of new technology real in an increasingly complex IT landscape. From database and systems management to Active Directory and Microsoft 365 migration and management, and cybersecurity resilience, Quest helps customers solve their next IT challenge now. Around the globe, more than 130,000 companies and 95% of the Fortune 500 count on Quest to deliver proactive management and monitoring for the next enterprise initiative, find the next solution for complex Microsoft challenges, and stay ahead of the next threat. For more information, visit Media contact:Slava BalykovPR in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Techday NZ
30-04-2025
- Business
- Techday NZ
Denodo updates platform with new data marketplace & GenAI tools
Denodo has introduced Denodo Platform 9.2, an updated version of its logical data management platform, incorporating a new data marketplace and expanded generative AI capabilities. The Denodo Platform 9.2 release is designed to provide business users with a data marketplace that emulates familiar e-commerce experiences, making it easier for users across various roles to discover, access, and use organisational data. The marketplace operates on Denodo's semantic layer, presenting business context for data, and employs AI-powered automation to assist with repetitive functions. The new marketplace also offers users a comprehensive overview of how data is being accessed within their organisations, indicating which dashboards and analytic tools are using specific data products. Organisations with teams in multiple countries can benefit from the user interface's support of multiple languages, allowing individuals to select their preferred UI language. Stewart Bond, Research Vice President at IDC, highlighted the platform's improved accessibility, stating, "The Denodo Data Catalog has always made data easier to access and use, even across organizations data lakehouse and supporting data sources, but I believe the new data marketplace functionality of Denodo Platform 9.2 makes access even more intuitive with a more user-friendly interface. Now, people with less or no technical knowledge of data catalogs can leverage the marketplace for data access with little or no guidance." Denodo Platform 9.2 includes enhancements for generative AI (GenAI) applications, building upon previous AI-focused updates. These enhancements are aimed at giving enterprises the capability to provide generative AI models with AI-ready data, ensuring high quality and governance. The release now allows for customisation of AI models with user-specific knowledge and improved support for unstructured data, facilitating tasks such as extracting sentiment from social media or analysing images. An additional component of the upgrade is a certification programme targeted at GenAI developers. The new features also expand on AI-focused tools introduced in the earlier 9.1 release, such as Denodo Assistant and the Denodo AI SDK, both designed to streamline the development of GenAI applications. Speaking about the impact of these AI tools, Barend Van Coller, Data Analyst and Data Governance Team Lead at Alexforbes, said, "With Denodo Assistant and its AI SDK, we've dramatically expanded access to governed data across Alexforbes. What was once the domain of IT and power users is now accessible to non-technical users through intuitive, conversational interactions. We're excited about the upcoming Denodo 9.2 release, which further empowers our teams to search, discover, and interact with data – securely and seamlessly." Developers constructing data products will find a series of updates aimed at fostering smooth collaboration while maintaining governance and efficiency. These updates include support for continuous integration and development processes, enabling branch-based workflows that allow teams to collaborate with greater flexibility. Automation features such as dependency analysis are intended to help cut down on errors and make data caching and curation more efficient. There is also enhanced support for open table formats, improving compatibility with platforms such as Databricks Unity Catalog and Snowflake's Open Catalog. Alberto Pan, Chief Technology Officer at Denodo, commented on the company's direction, saying, "By continuously evolving our capabilities in the areas of data-self service, data product development, and GenAI, Denodo is enabling enterprises to leverage data more effectively to enhance decision-making, automate complex workflows, and deliver more powerful services. These innovations will put organizations at the forefront of data-driven transformation, maximizing the impact of their data investments." Denodo reports that the Platform 9.2 update is intended to accelerate data product development and adoption of GenAI across industries, while continuing to provide expanded access, management, and oversight of organisational data assets.
