Latest news with #Cloudera
Channel Post MEA
7 hours ago
- Business
- Channel Post MEA
Cloudera Delivers AI-Powered Unified Data Visualization in On-Premises Data Centers
Cloudera has announced the latest release of Cloudera Data Visualization, extending its AI capabilities to customers operating in on-premises environments. This new offering is a high-performance AI tool that democratizes insights across the full data lifecycle. With Cloudera Data Visualization, data engineers, business analysts, and data scientists can seamlessly communicate, collaborate, and share insights, without compromising data security or governance – all through the common language of visualization. Enterprises often struggle to appropriately visualize data due to silos across multiple platforms, complex integrations, and data governance limitations. Without a unified view, data visualization can be incomplete or misleading, often resulting in ineffective decision-making. Cloudera Data Visualization, now available on-premises, provides secure and integrated AI capabilities native to the Cloudera platform, empowering organizations to self-service visualization across multi-cloud and hybrid environments and the entire data lifecycle. This enables users to now unlock the value of their on-prem data through intuitive, out-of-the-box picturing and natural language querying. With Cloudera Data Visualization, enterprises can move faster, more efficiently, and with increased collaboration. 'As enterprises continue to prioritize both multi-cloud and hybrid environments, they need to see their data as a part of a bigger picture,' says Leo Brunnick, Chief Product Officer at Cloudera. 'Bringing together AI-driven insights, secure infrastructure, and seamless collaboration in one unified platform, users can see the missing puzzle pieces of their data, wherever they may be. It's not just about being able to see the data; it's about seeing how it all fits together to deliver business-critical insights.' Key features of Cloudera Data Visualization include: Out-of-the-Box Imaging : Use an intuitive drag-and-drop builder or choose from a wide range of custom extension options to create graphs or charts for every use case—from customer loyalty shifts to decades' worth of trading trends—all in one platform. : Use an intuitive drag-and-drop builder or choose from a wide range of custom extension options to create graphs or charts for every use case—from customer loyalty shifts to decades' worth of trading trends—all in one platform. Built-in AI Tools : Leverage AI in your BI workflows with AI Visual, a built-in AI tool in Cloudera Data Visualization. Unlock visual and structured reports easily using natural language querying, making AI-driven insights more accessible than ever. : Leverage AI in your BI workflows with AI Visual, a built-in AI tool in Cloudera Data Visualization. Unlock visual and structured reports easily using natural language querying, making AI-driven insights more accessible than ever. Predictive Application Builder: Create unique applications with this innovative capability that is pre-built with machine learning models served in Cloudera AI, as well as models in Amazon Bedrock, OpenAI, and Microsoft Azure OpenAI. Create unique applications with this innovative capability that is pre-built with machine learning models served in Cloudera AI, as well as models in Amazon Bedrock, OpenAI, and Microsoft Azure OpenAI. Enterprise Security: Leverage enterprise data from anywhere without moving, copying, or creating security gaps with integrated security with Cloudera Shared Data Experience (SDX). Leverage enterprise data from anywhere without moving, copying, or creating security gaps with integrated security with Cloudera Shared Data Experience (SDX). Robust Governance: Take complete control of data used for picturing with advanced governance features. 'By integrating directly with Cloudera's unified platform, users benefit from a consistent experience, enhanced collaboration, and full lifecycle data exploration—all while retaining full control over their own infrastructure,' said industry analyst, Sanjeev Mohan. 'Now, Cloudera users can picture and share insights securely within their on-prem environment, allowing their teams to be more agile and informed in their decision-making.'
Business Insider
3 days ago
- Business
- Business Insider
How a nonprofit's AI tool is giving aid workers life-saving answers during humanitarian crises
For "CXO AI Playbook," Business Insider takes a look at mini case studies about AI adoption across industries, company sizes, and technology DNA. We've asked each of the featured companies to tell us about the problems they're trying to solve with AI, who's making these decisions internally, and their vision for using AI in the future. Founded in 1979, Mercy Corps is a global humanitarian aid organization based in Portland, Oregon. It operates in more than 40 countries, and has roughly 4,000 employees supporting communities affected by poverty, disaster, conflict, and the climate crisis. The majority of its staff members are from the countries where they work. Situation analysis: What problem was the organization trying to solve? In the developing world, agricultural crises like droughts, crop failures, and loss of livestock can rapidly escalate into humanitarian crises. Mercy Corps has experience anticipating these emergencies and reducing their impact. But a lack of timely, reliable data often prevents that knowledge from reaching the right people at the right time. Alicia Morrison, the director of data science at Mercy Corps, saw potential in generative AI for getting relevant information into the hands of decision-makers more quickly. The goal was to build a tool that could provide aid workers with quick, reliable answers to the day-to-day questions they face in the field. The answers would be based on past projects, research, and proven approaches, and include links to sources and citations so workers can know where the information comes from. "Making that tool available to the people doing the work helps them learn from what's been done and imagine new possibilities," she told Business Insider. "That's when we get the most creative ideas and uses of information." Key staff and partners Mercy Corps took part in Tech To the Rescue's AI for Changemakers program, a global accelerator that helps nonprofits experiment with AI. Through intensive, short-term training programs, Tech To the Rescue gives organizations a chance to pitch AI ideas and connect with private sector partners who can help bring them to life. Mercy Corps matched with Cloudera, a software company focused on data management, analytics, and AI. "They had the idea and we believed we could contribute our time, resources, and skills and add value," said Rob Dickens, a solutions architect at Cloudera. Cloudera donated engineering time and platform credits to develop the product, which is called the AI Methods Matcher. Dickens said development took about seven weeks, and the tool runs on Cloudera's AI Inference service, which uses Nvidia technology. AI in action Methods Matcher uses a type of generative AI called retrieval-augmented generation. It draws on an archive of successful projects to search for relevant information, summarize it, and offer recommendations. Now, decisions that aid workers make on the ground — from calculating vegetation health to tracking fertilizer distribution — can be guided by data. Morrison said the tool speeds up decision-making by reducing the time and manual research required to analyze large volumes of information. With Methods Matcher, Mercy Corps' teams can identify actions that have worked elsewhere and get evidence-based suggestions in real time. For example, in countries facing severe inflation, Mercy Corps often provides multipurpose cash assistance. But the organization needs to know the purchasing power of that cash to make an impact. In this case, an aid worker in the field might ask the tool, "How do I determine how much cash aid to give people in a region with rising inflation?" Methods Matcher responds with a tailored answer based on past Mercy Corps projects and research. Aid workers can ask follow-up questions in the same session, and because the tool "remembers" the conversation history, they can build on earlier questions without having to start over. The tool helps teams in the field quickly access information without waiting for support from HQ. "They can see for themselves how valuable this kind of information can be," Morrison said. Did it work, and how did leaders know? Since the tool's launch in November 2024, Morrison said that while they have yet to report metrics on the tool's impact, there has been strong early adoption among field teams. Mercy Corps is now working with Cloudera to expand Methods Matcher, develop new AI tools, and build data literacy across the organization. It's also gathering feedback on Methods Matcher from staff to understand what's working and what needs improvement. "We're a nonprofit, so we don't have a big team of in-house AI experts," Morrison said. "We're learning as we go — figuring out how to maintain these tools, how to evaluate them, and how to get people across the organization on board for the long haul." What's next? Mercy Corps has experienced a significant shift in funding in recent months, but Morrison said Methods Matcher and other AI tools remain "a priority investment area." She added that the organization will continue to improve based on team feedback. Dickens said Cloudera plans to bring agentic AI into the tool through its Agent Studio, automating tasks like gathering real-time data, analyzing trends, and generating reports or recommendations. This will allow Methods Matcher to surface relevant news and social media reports from affected areas, making it more responsive to events on the ground. "Aid workers will get richer, real-time context instead of manually compiling daily or monthly reports," he said.
Yahoo
24-05-2025
- Business
- Yahoo
Opinion - A make-or-break moment for the AI economy
As one of its first acts, the Trump administration in January signed Executive Order 14179, removing previous regulatory guardrails for artificial intelligence and placing the responsibility for this transformative technology squarely with the private sector. The private sector needs to embrace this duty, because the rapid development of so-called 'AI agents,' which promise to transform the way consumers travel, shop and even receive medical care, is going to demand cooperative industry action to ensure open and competitive markets. History has shown us that network effects — where the value of a platform grows as more people use it — can lead to significant market concentration. This dynamic can enable a small number of players to establish dominance and lead to high barriers to entry for newcomers. Artificial intelligence is fated to follow this same trend. In fact, we are at a critical juncture where the same dynamics that created digital monopolies in the past are beginning to take hold — only faster, and with broader implications. The next frontier of AI is not just what we see today: large language models or image generators. It is autonomous agents: AI systems acting on our behalf in everyday transactions. These agents will manage our schedules, compare insurance plans, negotiate purchases and more. They promise to make our lives easier by operating behind the scenes to save us time and money, and spare us cognitive load. And their adoption is happening quickly. A recent survey by Cloudera found that 96 percent of IT leaders plan to increase their use of AI agents in the coming year, with nearly half already seeing them as a key competitive advantage. Moreover, Walmart's announcement that it plans to start interfacing with AI shopping agents signals that we are already at the beginning of a structural shift in how decisions are made online. But the benefits of 'agentified' commerce won't materialize in full force unless we take affirmative steps to protect the promise of AI. Without standards to ensure open participation and fair competition, the agent-driven marketplace could become yet another closed system dominated by the few companies that have the resources and infrastructure to scale quickly. Smaller businesses could find themselves locked out. And consumers could find themselves at the mercy of hidden algorithms that aren't working in their best interests. Imagine this near-future scenario: you ask your AI assistant to plan a weekend trip to Napa Valley. It scans dozens of options, compares prices, negotiates availability, and returns with what seems like the best result. But what if it only considers providers that have exclusive deals or undisclosed business relationships with its parent company? What if smaller, independent options never even get a chance to compete? Now imagine this across other scenarios, such as finding a new healthcare provider or renegotiating your internet plan. History has shown that these fears are not speculative. But we've navigated similar challenges before. The internet as we know it runs on mostly open, decentralized standards that allow anyone to build and compete on a level playing field. In hardware, protocols such as USB, Wi-Fi and Bluetooth have enabled interoperability across brands and devices, helping innovation flourish without locking out newcomers. We should bring this same thinking to AI, and how the dynamic ecosystem of different AI tools and systems will interact — both with consumers and with each other. The future of AI-driven commerce demands open standards that ensure not just interoperability between agents but equitable access to marketplaces, so that a startup's offering can be just as discoverable as that of a global enterprise. One way to operationalize this vision is through the creation of a voluntary open AI agent registry. In this system, any business, regardless of size, could register its AI agents using standardized protocols. Consumer-facing AI assistants could query this registry to identify relevant service providers, ensuring that small players are part of the ecosystem from the start — and that agents are who they say they are, not scammers. In the case of travel, for instance, this would allow a locally owned B&B to appear in the same search as a multinational hotel chain. The user's agent could negotiate with both, compare deals, and surface the best option — not the one with the biggest marketing budget, or one that owns the cloud platform on which it is hosted. To make this happen, we need leadership, from both regulators and industry. Standards don't have to come from government mandates. In fact, many of the most successful ones have emerged from coalitions of private-sector leaders, academics and technologists, such as the Financial Data Exchange, which helped define open protocols for sharing consumer financial data securely across banks and fintechs. The benefits of getting this right are hard to overstate. Consumer trust is foundational, not just to AI adoption but to long-term confidence in digital systems that increasingly act on our behalf. For businesses, especially smaller ones, well-defined standards level the playing field and reduce integration hurdles, enabling broader participation in the digital economy. And for the broader ecosystem, it ensures a competitive, innovation-rich environment where value — not gatekeeping — wins. The best markets are free, open and competitive, and that should be true especially when transactions are handled by AI. We don't have to repeat the mistakes of the past. We can build an AI ecosystem that is open, competitive and fair from the start. But that requires intention, collaboration and urgency. e, and that should The AI economy is moving fast. Let's keep it moving in the right direction. Benjamin Wiener is the global head of Cognizant Moment, the digital and customer experience arm of U.S. professional services firm Cognizant. Copyright 2025 Nexstar Media, Inc. All rights reserved. This material may not be published, broadcast, rewritten, or redistributed.
The Hill
24-05-2025
- Business
- The Hill
A make-or-break moment for the AI economy
As one of its first acts, the Trump administration in January signed Executive Order 14179, removing previous regulatory guardrails for artificial intelligence and placing the responsibility for this transformative technology squarely with the private sector. The private sector needs to embrace this duty, because the rapid development of so-called 'AI agents,' which promise to transform the way consumers travel, shop and even receive medical care, is going to demand cooperative industry action to ensure open and competitive markets. History has shown us that network effects — where the value of a platform grows as more people use it — can lead to significant market concentration. This dynamic can enable a small number of players to establish dominance and lead to high barriers to entry for newcomers. Artificial intelligence is fated to follow this same trend. In fact, we are at a critical juncture where the same dynamics that created digital monopolies in the past are beginning to take hold — only faster, and with broader implications. The next frontier of AI is not just what we see today: large language models or image generators. It is autonomous agents: AI systems acting on our behalf in everyday transactions. These agents will manage our schedules, compare insurance plans, negotiate purchases and more. They promise to make our lives easier by operating behind the scenes to save us time and money, and spare us cognitive load. And their adoption is happening quickly. A recent survey by Cloudera found that 96 percent of IT leaders plan to increase their use of AI agents in the coming year, with nearly half already seeing them as a key competitive advantage. Moreover, Walmart's announcement that it plans to start interfacing with AI shopping agents signals that we are already at the beginning of a structural shift in how decisions are made online. But the benefits of 'agentified' commerce won't materialize in full force unless we take affirmative steps to protect the promise of AI. Without standards to ensure open participation and fair competition, the agent-driven marketplace could become yet another closed system dominated by the few companies that have the resources and infrastructure to scale quickly. Smaller businesses could find themselves locked out. And consumers could find themselves at the mercy of hidden algorithms that aren't working in their best interests. Imagine this near-future scenario: you ask your AI assistant to plan a weekend trip to Napa Valley. It scans dozens of options, compares prices, negotiates availability, and returns with what seems like the best result. But what if it only considers providers that have exclusive deals or undisclosed business relationships with its parent company? What if smaller, independent options never even get a chance to compete? Now imagine this across other scenarios, such as finding a new healthcare provider or renegotiating your internet plan. History has shown that these fears are not speculative. But we've navigated similar challenges before. The internet as we know it runs on mostly open, decentralized standards that allow anyone to build and compete on a level playing field. In hardware, protocols such as USB, Wi-Fi and Bluetooth have enabled interoperability across brands and devices, helping innovation flourish without locking out newcomers. We should bring this same thinking to AI, and how the dynamic ecosystem of different AI tools and systems will interact — both with consumers and with each other. The future of AI-driven commerce demands open standards that ensure not just interoperability between agents but equitable access to marketplaces, so that a startup's offering can be just as discoverable as that of a global enterprise. One way to operationalize this vision is through the creation of a voluntary open AI agent registry. In this system, any business, regardless of size, could register its AI agents using standardized protocols. Consumer-facing AI assistants could query this registry to identify relevant service providers, ensuring that small players are part of the ecosystem from the start — and that agents are who they say they are, not scammers. In the case of travel, for instance, this would allow a locally owned B&B to appear in the same search as a multinational hotel chain. The user's agent could negotiate with both, compare deals, and surface the best option — not the one with the biggest marketing budget, or one that owns the cloud platform on which it is hosted. To make this happen, we need leadership, from both regulators and industry. Standards don't have to come from government mandates. In fact, many of the most successful ones have emerged from coalitions of private-sector leaders, academics and technologists, such as the Financial Data Exchange, which helped define open protocols for sharing consumer financial data securely across banks and fintechs. The benefits of getting this right are hard to overstate. Consumer trust is foundational, not just to AI adoption but to long-term confidence in digital systems that increasingly act on our behalf. For businesses, especially smaller ones, well-defined standards level the playing field and reduce integration hurdles, enabling broader participation in the digital economy. And for the broader ecosystem, it ensures a competitive, innovation-rich environment where value — not gatekeeping — wins. The best markets are free, open and competitive, and that should be true especially when transactions are handled by AI. We don't have to repeat the mistakes of the past. We can build an AI ecosystem that is open, competitive and fair from the start. But that requires intention, collaboration and urgency. e, and that should The AI economy is moving fast. Let's keep it moving in the right direction. Benjamin Wiener is the global head of Cognizant Moment, the digital and customer experience arm of U.S. professional services firm Cognizant.
Techday NZ
23-05-2025
- Business
- Techday NZ
Cloudera adds AI & secure visualisation to on-prem data tools
Cloudera has announced the extension of its Data Visualization capability to on-premises environments, offering integrated AI tools and secure access for enterprises managing data across hybrid and multi-cloud infrastructures. The updated Cloudera Data Visualization service provides organisations with a platform for self-service data visualisation, allowing users to generate insights from on-premises data through out-of-the-box picturing and natural language querying. This development is intended to address challenges enterprises face in visualising data held in silos across multiple platforms, as well as issues related to complex integration and data governance. Data engineers, business analysts, and data scientists can now access integrated AI visualisation features within the Cloudera platform, enabling them to communicate, collaborate, and share data insights without compromising security or governance. The ability to gain a secure, unified view aims to prevent incomplete or misleading visualisation results, which can hinder effective decision-making within organisations. Cloudera highlighted the key features included in the on-premises release. Out-of-the-box imaging is supported via an intuitive drag-and-drop builder and a suite of custom extension options for creating graphs and charts appropriate for diverse use cases such as customer loyalty tracking and analysing long-term trading trends. The platform includes built-in AI tools, such as AI Visual, which allow users to leverage natural language querying to unlock visual and structured reports. This feature integrates AI directly into business intelligence workflows, designed to make AI-driven insights more accessible across an organisation. The Predictive Application Builder enables the creation of bespoke applications built on machine learning models available in Cloudera AI, Amazon Bedrock, OpenAI, and Microsoft Azure OpenAI. This capability allows organisations to deploy and use predictive models within their data visualisation processes. Cloudera Data Visualization maintains enterprise security standards through integration with the Cloudera Shared Data Experience (SDX). This means organisations can leverage data from any location without moving, copying, or exposing information to security gaps. Additionally, the platform offers robust governance tools that provide full control over the data used in visualisation projects. Addressing the significance of this development, Leo Brunnick, Chief Product Officer at Cloudera, said: "As enterprises continue to prioritise both multi-cloud and hybrid environments, they need to see their data as a part of a bigger picture. Bringing together AI-driven insights, secure infrastructure, and seamless collaboration in one unified platform, users can see the missing puzzle pieces of their data, wherever they may be. It's not just about being able to see the data; it's about seeing how it all fits together to deliver business-critical insights." Industry analyst Sanjeev Mohan commented on the release: "By integrating directly with Cloudera's unified platform, users benefit from a consistent experience, enhanced collaboration, and full lifecycle data exploration - all while retaining full control over their own infrastructure. Now, Cloudera users can picture and share insights securely within their on-prem environment, allowing their teams to be more agile and informed in their decision-making." Cloudera's Data Visualization is available for deployment across multi-cloud and hybrid infrastructures, intended to support improved collaboration and decision-making processes for enterprise clients managing complex data ecosystems.
