talk-data.com
Activities & events
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WEBINAR "What’s Next: The AI Trends Shaping 2026"
2025-12-30 · 17:00
Pre-Registration is REQUIRED. Add to your calendar - https://hubs.li/Q03Xdlc80 The pace of AI innovation is not slowing down—it’s accelerating. As we look ahead to 2026, the foundational shifts brought by generative AI are maturing into an era of Agentic Systems, Domain-Specific Models, and a profound redefinition of the AI Workforce. Join Sheamus McGovern, Founder of ODSC AI and Venture Partner/Head of AI at Cortical Ventures, for a high-impact 45-minute keynote that cuts through the hype to reveal the strategic AI trends that will define business and technology over the next year. Drawing on his unique perspective from leading one of the world’s top AI conferences and investing in the most promising AI startups, Sheamus will provide a tactical roadmap for where the real value—and the next competitive advantage—will emerge. Useful Links
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WEBINAR "What’s Next: The AI Trends Shaping 2026"
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WEBINAR "What’s Next: The AI Trends Shaping 2026"
2025-12-30 · 17:00
Pre-Registration is REQUIRED. Add to your calendar - https://hubs.li/Q03Xdlc80 The pace of AI innovation is not slowing down—it’s accelerating. As we look ahead to 2026, the foundational shifts brought by generative AI are maturing into an era of Agentic Systems, Domain-Specific Models, and a profound redefinition of the AI Workforce. Join Sheamus McGovern, Founder of ODSC AI and Venture Partner/Head of AI at Cortical Ventures, for a high-impact 45-minute keynote that cuts through the hype to reveal the strategic AI trends that will define business and technology over the next year. Drawing on his unique perspective from leading one of the world’s top AI conferences and investing in the most promising AI startups, Sheamus will provide a tactical roadmap for where the real value—and the next competitive advantage—will emerge. Useful Links
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WEBINAR "What’s Next: The AI Trends Shaping 2026"
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WEBINAR "What’s Next: The AI Trends Shaping 2026"
2025-12-30 · 17:00
Pre-Registration is REQUIRED. Add to your calendar - https://hubs.li/Q03Xdlc80 The pace of AI innovation is not slowing down—it’s accelerating. As we look ahead to 2026, the foundational shifts brought by generative AI are maturing into an era of Agentic Systems, Domain-Specific Models, and a profound redefinition of the AI Workforce. Join Sheamus McGovern, Founder of ODSC AI and Venture Partner/Head of AI at Cortical Ventures, for a high-impact 45-minute keynote that cuts through the hype to reveal the strategic AI trends that will define business and technology over the next year. Drawing on his unique perspective from leading one of the world’s top AI conferences and investing in the most promising AI startups, Sheamus will provide a tactical roadmap for where the real value—and the next competitive advantage—will emerge. Useful Links
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WEBINAR "What’s Next: The AI Trends Shaping 2026"
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WEBINAR "What’s Next: The AI Trends Shaping 2026"
2025-12-30 · 17:00
Pre-Registration is REQUIRED. Add to your calendar - https://hubs.li/Q03Xdlc80 The pace of AI innovation is not slowing down—it’s accelerating. As we look ahead to 2026, the foundational shifts brought by generative AI are maturing into an era of Agentic Systems, Domain-Specific Models, and a profound redefinition of the AI Workforce. Join Sheamus McGovern, Founder of ODSC AI and Venture Partner/Head of AI at Cortical Ventures, for a high-impact 45-minute keynote that cuts through the hype to reveal the strategic AI trends that will define business and technology over the next year. Drawing on his unique perspective from leading one of the world’s top AI conferences and investing in the most promising AI startups, Sheamus will provide a tactical roadmap for where the real value—and the next competitive advantage—will emerge. Useful Links
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WEBINAR "What’s Next: The AI Trends Shaping 2026"
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WEBINAR "What’s Next: The AI Trends Shaping 2026"
2025-12-30 · 17:00
Pre-Registration is REQUIRED. Add to your calendar - https://hubs.li/Q03Xdlc80 The pace of AI innovation is not slowing down—it’s accelerating. As we look ahead to 2026, the foundational shifts brought by generative AI are maturing into an era of Agentic Systems, Domain-Specific Models, and a profound redefinition of the AI Workforce. Join Sheamus McGovern, Founder of ODSC AI and Venture Partner/Head of AI at Cortical Ventures, for a high-impact 45-minute keynote that cuts through the hype to reveal the strategic AI trends that will define business and technology over the next year. Drawing on his unique perspective from leading one of the world’s top AI conferences and investing in the most promising AI startups, Sheamus will provide a tactical roadmap for where the real value—and the next competitive advantage—will emerge. Useful Links
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WEBINAR "What’s Next: The AI Trends Shaping 2026"
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Can Multimodal AI Redefine Productivity in 2026?
2025-12-18 · 17:00
Free Live Webinar - Can Multimodal AI Redefine Productivity in 2026? AI is advancing at record speed and the next major shift is Multimodal AI, where systems can process text, images, audio, and more in a unified way. This breakthrough is reshaping how teams work, innovate, and make smarter decisions. Join us for an insightful 60-minute live session to discover how multimodal AI is transforming productivity, accelerating workflows, and creating new advantages for forward-thinking organizations. Date: Thu, Dec 18, 2025 Time: 12 PM EST \| 60 minutes Save Your Seat - Register Now In this session, you’ll learn:
Whether you're a business leader, IT professional, or AI enthusiast, this webinar will give you the insights needed to stay ahead of this rapidly evolving AI revolution. Reserve your free spot now - limited seats available! |
Can Multimodal AI Redefine Productivity in 2026?
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Can Multimodal AI Redefine Productivity in 2026?
2025-12-18 · 17:00
Free Live Webinar - Can Multimodal AI Redefine Productivity in 2026? AI is advancing at record speed and the next major shift is Multimodal AI, where systems can process text, images, audio, and more in a unified way. This breakthrough is reshaping how teams work, innovate, and make smarter decisions. Join us for an insightful 60-minute live session to discover how multimodal AI is transforming productivity, accelerating workflows, and creating new advantages for forward-thinking organizations. Date: Thu, Dec 18, 2025 Time: 12 PM EST \| 60 minutes Save Your Seat - Register Now In this session, you’ll learn:
Whether you're a business leader, IT professional, or AI enthusiast, this webinar will give you the insights needed to stay ahead of this rapidly evolving AI revolution. Reserve your free spot now - limited seats available! |
Can Multimodal AI Redefine Productivity in 2026?
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183 - Part II: Designing with the Flow of Work: Accelerating Sales in B2B Analytics and AI Products by Minimizing Behavior Change
2025-11-27 · 02:00
Brian T. O’Neill
– host
In this second part of my three-part series (catch Part I via episode 182), I dig deeper into the key idea that sales in commercial data products can be accelerated by designing for actual user workflows—vs. going wide with a “many-purpose” AI and analytics solution that “does more,” but is misaligned with how users’ most important work actually gets done. To explain this, I will explain the concept of user experience (UX) outcomes, and how building your solution to enable these outcomes may be a dependency for you to get sales traction, and for your customer to see the value of your solution. I also share practical steps to improve UX outcomes in commercial data products, from establishing a baseline definition of UX quality to mapping out users’ current workflows (and future ones, when agentic AI changes their job). Finally, I talk about how approaching product development as small “bets” helps you build small, and learn fast so you can accelerate value creation. Highlights/ Skip to: Continuing the journey: designing for users, workflows, and tasks (00:32) How UX impacts sales—not just usage and adoption(02:16) Understanding how you can leverage users’ frustrations and perceived risks as fuel for building an indispensable data product (04:11) Definition of a UX outcome (7:30) Establishing a baseline definition of product (UX) quality, so you know how to observe and measure improvement (11:04 ) Spotting friction and solving the right customer problems first (15:34) Collecting actionable user feedback (20:02) Moving users along the scale from frustration to satisfaction to delight (23:04) Unique challenges of designing B2B AI and analytics products used for decision intelligence (25:04) Quotes from Today’s Episode One of the hardest parts of building anything meaningful, especially in B2B or data-heavy spaces, is pausing long enough to ask what the actual ‘it’ is that we’re trying to solve. People rush into building the fix, pitching the feature, or drafting the roadmap before they’ve taken even a moment to define what the user keeps tripping over in their day-to-day environment. And until you slow down and articulate that shared, observable frustration, you’re basically operating on vibes and assumptions instead of behavior and reality. What you want is not a generic problem statement but an agreed-upon description of the two or three most painful frictions that are obvious to everyone involved, frictions the user experiences visibly and repeatedly in the flow of work. Once you have that grounding, everything else prioritization, design decisions, sequencing, even organizational alignment suddenly becomes much easier because you’re no longer debating abstractions, you’re working against the same measurable anchor. And the irony is, the faster you try to skip this step, the longer the project drags on, because every downstream conversation becomes a debate about interpretive language rather than a conversation about a shared, observable experience. __ Want people to pay for your product? Solve an observable problem—not a vague information or data problem. What do I mean? “When you’re trying to solve a problem for users, especially in analytical or AI-driven products, one of the biggest traps is relying on interpretive statements instead of observable ones. Interpretive phrasing like ‘they’re overwhelmed’ or ‘they don’t trust the data’ feels descriptive, but it hides the important question of what, exactly, we can see them doing that signals the problem. If you can’t film it happening, if you can’t watch the behavior occur in real time, then you don’t actually have a problem definition you can design around. Observable frustration might be the user jumping between four screens, copying and pasting the same value into different systems, or re-running a query five times because something feels off even though they can’t articulate why. Those concrete behaviors are what allow teams to converge and say, ‘Yes, that’s the thing, that is the friction we agree must change,’ and that shift from interpretation to observation becomes the foundation for better design, better decision-making, and far less wasted effort. And once you anchor the conversation in visible behavior, you eliminate so many circular debates and give everyone, from engineering to leadership, a shared starting point that’s grounded in reality instead of theory." __ One of the reasons that measuring the usability/utility/satisfaction of your product’s UX might seem hard is that you don’t have a baseline definition of how satisfactory (or not) the product is right now. As such, it’s very hard to tell if you’re just making product changes—or you’re making improvements that might make the product worth paying for at all, worth paying more for, or easier to buy. "It’s surprisingly common for teams to claim they’re improving something when they’ve never taken the time to document what the current state even looks like. If you want to create a meaningful improvement, something a user actually feels, you need to understand the baseline level of friction they tolerate today, not what you imagine that friction might be. Establishing a baseline is not glamorous work, but it’s the work that prevents you from building changes that make sense on paper but do nothing to the real flow of work. When you diagram the existing workflow, when you map the sequence of steps the user actually takes, the mismatches between your mental model and their lived experience become crystal clear, and the design direction becomes far less ambiguous. That act of grounding yourself in the current state allows every subsequent decision, prioritizing fixes, determining scope, measuring progress, to be aligned with reality rather than assumptions. And without that baseline, you risk designing solutions that float in conceptual space, disconnected from the very pains you claim to be addressing." __ Prototypes are a great way to learn—if you’re actually treating them as a means to learn, and not a product you intend to deliver regardless of the feedback customers give you. "People often think prototyping is about validating whether their solution works, but the deeper purpose is to refine the problem itself. Once you put even a rough prototype in front of someone and watch what they do with it, you discover the edges of the problem more accurately than any conversation or meeting can reveal. Users will click in surprising places, ignore the part you thought mattered most, or reveal entirely different frictions just by trying to interact with the thing you placed in front of them. That process doesn’t just improve the design, it improves the team’s understanding of which parts of the problem are real and which parts were just guesses. Prototyping becomes a kind of externalization of assumptions, forcing you to confront whether you’re solving the friction that actually holds back the flow of work or a friction you merely predicted. And every iteration becomes less about perfecting the interface and more about sharpening the clarity of the underlying problem, which is why the teams that prototype early tend to build faster, with better alignment, and far fewer detours." __ Most founders and data people tend to measure UX quality by “counting usage” of their solution. Tracking usage stats, analytics on sessions, etc. The problem with this is that it tells you nothing useful about whether people are satisfied (“meets spec”) or delighted (“a product they can’t live without”). These are product metrics—but they don’t reflect how people feel. There are better measurements to use for evaluating users’ experience that go beyond “willingness to pay.” Payment is great, but in B2B products, buyers aren’t always users—and we’ve all bought something based on the promise of what it would do for us, but the promise fell short. "In B2B analytics and AI products, the biggest challenge isn’t complexity, it’s ambiguity around what outcome the product is actually responsible for changing. Teams often define success in terms of internal goals like ‘adoption,’ ‘usage,’ or ‘efficiency,’ but those metrics don’t tell you what the user’s experience is supposed to look like once the product is working well. A product tied to vague business outcomes tends to drift because no one agrees on what the improvement should feel like in the user’s real workflow. What you want are visible, measurable, user-centric outcomes, outcomes that describe how the user’s behavior or experience will change once the solution is in place, down to the concrete actions they’ll no longer need to take. When you articulate outcomes at that level, it forces the entire organization to align around a shared target, reduces the scope bloat that normally plagues enterprise products, and gives you a way to evaluate whether you’re actually removing friction rather than just adding more layers of tooling. And ironically, the clearer the user outcome is, the easier it becomes to achieve the business outcome, because the product is no longer floating in abstraction, it’s anchored in the lived reality of the people who use it." Links Listen to part one: Episode 182 Schedule a Design-Eyes Assessment with me and get clarity, now. |
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182 - Designing with the Flow of Work: Accelerating Sales in B2B Analytics and AI Products by Minimizing Behavior Change
2025-11-10 · 08:00
Brian T. O’Neill
– host
Building B2B analytics and AI tools that people will actually pay for and use is hard. The reality is, your product won’t deliver ROI if no one’s using it. That’s why first principles thinking says you have to solve the usage problem first. In this episode, I’ll explain why the key to user adoption is designing with the flow of work—building your solution around the natural workflows of your users to minimize the behavior changes you’re asking them to make. When users clearly see the value in your product, it becomes easier to sell and removes many product-related blockers along the way. We’ll explore how product design impacts sales, the difference between buyers and users in enterprise contexts, and why challenging the “data/AI-first” mindset is essential. I’ll also share practical ways to align features with user needs, reduce friction, and drive long-term adoption and impact. If you’re ready to move beyond the dashboard and start building products that truly fit the way people work, this episode is for you. Highlights/Skip to: The core argument: why solving for user adoption first helps demonstrate ROI and facilitate sales in B2B analytics and AI products (1:34) How showing the value to actual end users—not just buyers—makes it easier to sell your product (2:33) Why designing for outcomes instead of outputs (dashboards, etc) leads to better adoption and long-term product value (8:16) How to “see” beyond users’ surface-level feature requests and solutions so you can solve for the actual, unspoken need—leading to an indispensable product (10:23) Reframing feature requests as design-actionable problems (12:07) Solving for unspoken needs vs. customer-requested features and functions (15:51) Why “disruption” is the wrong approach for product development (21:19) Quotes: “Customers’ tolerance for poorly designed B2B software has decreased significantly over the last decade. People now expect enterprise tools to function as smoothly and intuitively as the consumer apps they use every day. Clunky software that slows down workflows is no longer acceptable, regardless of the data it provides. If your product frustrates users or requires extra effort to achieve results, adoption will suffer. Even the most powerful AI or analytics engine cannot compensate for a confusing or poorly structured interface. Enterprises now demand experiences that are seamless, efficient, and aligned with real workflows. This shift means that product design is no longer a secondary consideration; it is critical to commercial success. Founders and product leaders must prioritize usability, clarity, and delight in every interaction. Software that is difficult to use increases the risk of churn, lengthens sales cycles, and diminishes perceived value. Products must anticipate user needs and deliver solutions that integrate naturally into existing workflows. The companies that succeed are the ones that treat user experience as a strategic differentiator. Ignoring this trend creates friction, frustration, and missed opportunities for adoption and revenue growth. Design quality is now inseparable from product value and market competitiveness. The message is clear: if you want your product to be adopted, retain customers, and win in the market, UX must be central to your strategy.” — “No user really wants to ‘check a dashboard’ or use a feature for its own sake. Dashboards, charts, and tables are outputs, not solutions. What users care about is completing their tasks, solving their problems, and achieving meaningful results. Designing around workflows rather than features ensures your product is indispensable. A workflow-first approach maps your solution to the actual tasks users perform in the real world. When we understand the jobs users need to accomplish, we can build products that deliver real value and remove friction. Focusing solely on features or data can create bloated products that users ignore or struggle to use. Outputs are meaningless if they do not fit into the context of a user’s work. The key is to translate user needs into actionable workflows and design every element to support those flows. This approach reduces cognitive load, improves adoption, and ensures the product's ROI is realized. It also allows you to anticipate challenges and design solutions that make workflows smoother, faster, and more efficient. By centering design on actual tasks rather than arbitrary metrics, your product becomes a tool users can’t imagine living without. Workflow-focused design directly ties to measurable outcomes for both end users and buyers. It shifts the conversation from features to value, making adoption, satisfaction, and revenue more predictable.” — “Just because a product is built with AI or powerful data capabilities doesn’t mean anyone will adopt it. Long-term value comes from designing solutions that users cannot live without. It’s about creating experiences that take people from frustration to satisfaction to delight. Products must fit into users’ natural workflows and improve their performance, efficiency, and outcomes. Buyers' perceived ROI is closely tied to meaningful adoption by end users. If users struggle, churn rises, and financial impact is diminished, regardless of technical sophistication. Designing for delight ensures that the product becomes a positive force in the user’s daily work. It strengthens engagement, reduces friction, and builds customer loyalty. High-quality UX allows the product to demonstrate value automatically, without constant explanations or hand-holding. Delightful experiences encourage advocacy, referrals, and easier future sales. The real power of design lies in aligning technical capabilities with human behavior and workflow. When done correctly, this approach transforms a tool into an indispensable part of the user’s job and a demonstrable asset for the business. Focusing on usability, satisfaction, and delight creates long-term adoption and retention, which is the ultimate measure of product success.” — “Your product should enter the user’s work stream like a raft on a river, moving in the same direction as their workflow. Users should not have to fight the current or stop their flow to use your tool. Introducing friction or requiring users to change their behavior increases risk, even if the product delivers ROI. The more naturally your product aligns with existing workflows, the easier it is to adopt and the more likely it is to be retained. Products that feel intuitive and effortless become indispensable, reducing conversations about usability during demos. By matching the flow of work, your solution improves satisfaction, accelerates adoption, and enhances perceived value. Disrupting workflows without careful observation can create new problems, frustrate users, and slow down sales. The goal is to move users from frustration to satisfaction to delight, all while achieving the intended outcomes. Designing with the flow of work ensures that every feature, interface element, and interaction fits seamlessly into the tasks users already perform. It allows users to focus on value instead of figuring out how to use the product. This alignment is key to unlocking adoption, retaining customers, and building long-term loyalty. Products that resist the natural workflow may demonstrate ROI on paper but fail in practice due to friction and low engagement. Success requires designing a product that supports the user’s journey downstream without interruption or extra effort. When you achieve this, adoption becomes easier, sales conversations smoother, and long-term retention higher.” — |
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Building Enterprise AI: Inside Cloudaeon’s RAG, MCP and Agentic Frameworks
2025-11-05 · 14:00
Artificial intelligence is rapidly evolving from experimentation to enterprise scale engineering. Yet many organisations struggle to turn AI pilots into governed and reliable operational systems. Models work in silos, starving context and control, while fragmented data and disconnected tools add layers of complexity. Recent studies show that while nearly 8 in 10 enterprises are experimenting with AI, only a few are successful. Instead of accelerating transformation, AI ends up slowing it. This leaves leaders searching for a way to unify intelligence and governed data into one integrated system. At Cloudaeon, we help enterprises close that gap. Our Data and AI leaders have built practical frameworks that make AI easier to scale and manage, turning scattered initiatives into a connected system where intelligence and automation work together. Featuring guest speaker: Rajkumar Manoharan- Chief Architect,Cloudaeon Amol Malpani- CTO, Cloudaeon Ashutosh Suryawanshi- Lead AI Engineer, Cloudaeon In this webinar, you’ll see in action:
Together, these form the foundation of an intelligent enterprise, one where AI is transparent and built for scale. With Cloudaeon’s experience in enterprise delivery, you can move from isolated experiments to real business impact with confidence. Submit your use case and get a free AI Proof of Concept. See how Cloudaeon can turn your ideas into enterprise scale results. |
Building Enterprise AI: Inside Cloudaeon’s RAG, MCP and Agentic Frameworks
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Accelerating Data Success: Three Essential lessons from Edmund Optics' Fast-Paced Innovation Drive
2025-09-24 · 11:20
David Rice
– CEO
@ Snap Analytics
,
Daniel Adams
– Global Analytics Manager
@ Edmund Optics
,
Calvin Fuss
– Head of AI
@ Snap Analytics
Edmund Optics stands at the forefront of advanced manufacturing, distributing more than 34,000 products and customised solutions in optics, photonics and imaging to a range of industries across the globe. Just a year ago, Edmund Optics began an ambitious journey to transform its data science capabilities, aiming to use Machine Learning (ML) and AI to deliver real value to their business and customers. Join us for an engaging panel discussion featuring Daniel Adams, Global Analytics Manager at Edmund Optics, as he shares the company's remarkable transformation from having no formal data science capabilities to deploying multiple ML and AI models in production—all within just 12 months. Daniel will highlight how Edmund Optics cultivated internal enthusiasm for data solutions, built trust, and created momentum to push the boundaries of what’s possible with data. In this session, Daniel will reveal three key lessons learned on the journey from “data zero” to “data hero.” If you’re navigating a similar path, don’t miss this opportunity to discover actionable insights and strategies that can empower your own internal data initiatives. |
Big Data LDN 2025
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Microsoft Fabric Thursday Expert Series - 2025
2025-09-11 · 12:30
Session Title: AI-Powered Insights: Boosting Data Performance Across Enterprise Fabric Stacks Session Description: Artificial Intelligence (AI) is accelerating data performance across Microsoft-centric enterprise environments, transforming how organizations visualize, analyze, and act on data. This session delivers real-world insights on AI integration across four critical pillars: data visualization, AutoML, unified analytics platforms, and large language models (LLMs). Drawing from cross-sector case studies, we’ll examine how AI-augmented tools like natural language queries, smart dashboards, and anomaly detection enhance Microsoft Fabric experiences enabling faster, more inclusive decision-making. AutoML platforms are streamlining model development, reducing time-to-value by over 50% in business scenarios ranging from sales forecasting to quality control. Integrated analytics solutions minimize data prep and accelerate insight delivery by up to 70%, with Fabric’s end-to-end tooling serving as a foundation for scalable automation. We also explore how LLMs elevate accessibility through conversational interfaces and intelligent code generation improving exploration and productivity across roles. While AI unlocks tangible benefits, we’ll also address key limitations including data governance and model oversight. Attendees will gain actionable guidance on evaluating and operationalizing AI capabilities within their existing Microsoft Fabric ecosystem to drive measurable improvements in data-driven outcomes. Be Ready to Engage: Bring a notepad – this is a content-rich session! Submit your questions beforehand via Comments. Ask questions live via comments or join the stage with camera/mic access – just reach out to us in advance if you’d like to participate on screen. Email: [email protected] |
Microsoft Fabric Thursday Expert Series - 2025
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#308 A Framework for GenAI App and Agent Development with Jerry Liu, CEO at LlamaIndex
2025-06-30 · 10:00
The enterprise adoption of AI agents is accelerating, but significant challenges remain in making them truly reliable and effective. While coding assistants and customer service agents are already delivering value, more complex document-based workflows require sophisticated architectures and data processing capabilities. How do you design agent systems that can handle the complexity of enterprise documents with their tables, charts, and unstructured information? What's the right balance between general reasoning capabilities and constrained architectures for specific business tasks? Should you centralize your agent infrastructure or purchase vertical solutions for each department? The answers lie in understanding the fundamental trade-offs between flexibility, reliability, and the specific needs of your organization. Jerry Liu is the CEO and Co-founder at LlamaIndex, the AI agents platform for automating document workflows. Previously, he led the ML monitoring team at Robust Intelligence, did self-driving AI research at Uber ATG, and worked on recommendation systems at Quora. In the episode, Richie and Jerry explore the readiness of AI agents for enterprise use, the challenges developers face in building these agents, the importance of document processing and data structuring, the evolving landscape of AI agent frameworks like LlamaIndex, and much more. Links Mentioned in the Show: LlamaIndexLlamaIndex Production Ready Framework For LLM AgentsTutorial: Model Context Protocol (MCP)Connect with JerryCourse: Retrieval Augmented Generation (RAG) with LangChainRelated Episode: RAG 2.0 and The New Era of RAG Agents with Douwe Kiela, CEO at Contextual AI & Adjunct Professor at Stanford UniversityRewatch RADAR AI New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business |
DataFramed |
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Why Distributed SQL's Moment Has Arrived
2025-06-25 · 17:00
👉 Register here 👈 The future of data architecture is already here: distributed, cloud-native, and AI-ready. Is your organization equipped to meet the moment? Join leading data experts Sanjeev Mohan, Dave Burgess, and Mark Donsky for a live panel discussion on why distributed SQL has become a critical building block for modern data platforms—and what that means for companies struggling with the limits of traditional databases, sharding complexity, and patchwork scalability. The panel will unpack the macro trends accelerating adoption of distributed SQL, including the surge in data-intensive applications, demand for real-time analytics, elastic scalability, cost pressure, and the rise of AI workloads. You’ll hear firsthand how enterprises and SaaS innovators are overcoming the limitations of legacy databases, simplifying operations, and unlocking new AI-driven capabilities with distributed SQL solutions like TiDB. You’ll gain practical perspectives on:
Whether you’re a CTO, architect, or data engineering leader, this discussion will equip you with the knowledge to assess how distributed SQL fits into your organization’s modernization journey. Register now to secure your spot! 👉 Register here 👈 |
Why Distributed SQL's Moment Has Arrived
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(ONLINE WEBINAR) Accelerating AI Readiness in Financial Services
2025-06-05 · 15:00
Accelerating AI Readiness in Financial Services: From Data Foundations to Real-World Impact Join Celestial Systems for a 30-minute live session designed for financial services leaders looking to operationalize AI initiatives with speed, scale, and success. Discover how to build strong data foundations and move from AI planning to production with confidence. In this session, Jordan Nelson, Senior AI and Software Architect at Celestial Systems, will walk through practical approaches to preparing financial services data systems for scalable AI success. You’ll learn how to modernize your stack, improve data quality, and accelerate transformation with tools like Microsoft Fabric and Dataiku. We will cover:
Why Attend? Whether you’re just beginning to explore AI or already piloting solutions, this session will equip you with frameworks, tools, and ideas to turn fragmented data into business intelligence—faster and with less friction. Celestial: Empowering Enterprises Since 2001 Based in Vancouver, Canada with worldwide offices and a fully in-house engineering team, we combine a heritage of industry leadership in application engineering with deep expertise in data and AI solutions. At Celestial, we’re passionate about empowering enterprises to leverage the power of AI to unlock new opportunities, minimize risk, and sharpen their competitive edge. |
(ONLINE WEBINAR) Accelerating AI Readiness in Financial Services
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#304 Accelerating Data Science with Nick Becker, Technical Product Manager at NVIDIA & Dan Hannah, Associate Director at SES AI
2025-06-02 · 10:00
Dan Hannah
– Associate Director
@ SES AI Corporation
,
Richie
– host
@ DataCamp
,
Nick Becker
– Group Product Manager
@ NVIDIA
GPU acceleration is transforming how data scientists tackle computationally intensive problems in the AI and materials science fields. When dealing with billions of potential molecular combinations or massive datasets requiring dimensionality reduction, traditional CPU approaches often become prohibitively slow and expensive. How can data professionals determine when GPU acceleration will provide meaningful benefits to their workflows? Understanding the right applications for this technology can mean the difference between waiting hours versus minutes for critical results. Nick Becker is a Group Product Manager at NVIDIA, focused on building RAPIDS and the broader accelerated data science ecosystem. Nick has a professional background in technology and government. Prior to NVIDIA, he worked at Enigma Technologies, a data science startup. Before Enigma, he conducted economics research and forecasting at the Federal Reserve Board of Governors, the central bank of the United States. Dan Hannah is an Associate Director at SES AI Corporation. At SES, Dan leads a research program focused on discovering new battery materials using machine learning, chemical informatics, and physics-driven simulations. Prior to joining SES, Dan spent several years as a data scientist in the cybersecurity industry. Dan holds a Ph.D. in Physical Chemistry from Northwestern University and did a postdoctoral fellowship at Berkeley National Lab, where his focus was the discovery of novel inorganic materials for energy applications. In the episode, Richie, Nick, and Dan explore the quest for new battery technologies, the role of data science and machine learning in material discovery, the integration of NVIDIA's GPU technology, the balance between computational simulations and lab work, and much more. Links Mentioned in the Show: NVIDIA RAPIDSSES AI CorporationConnect with Dan and NickCareer Track: Machine Learning Scientist in PythonRelated Episode: Data Science Trends from 2 Kaggle Grandmasters with Jean-Francois Puget, Distinguished Engineer at NVIDIA & Chris Deotte, Senior Data Scientist at NVIDIARewatch sessions from RADAR: Skills Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business |
DataFramed |
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Scott Schwaitzberg
– Sr. Asset Leader
@ McKinsey & Company
,
Jack Keenan
– Manager of Software Engineering
@ McKinsey
Explore the journey behind building the McKinsey Value Intelligence Assistant, bringing AI powered curation and insights to key business leaders by integrating dozens of datasets, filings and earnings call transcripts from 50K global companies. Gain insights into overcoming challenges in system architecture, data security, and real-time analytics to create a robust, cloud-native data intelligence platform with a small team in a short period time and the resulting business impact! This Session is hosted by a Google Cloud Next Sponsor. |
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North America's business leaders on the AI revolution and verticalization
2025-04-08 · 18:45
Brian Goldstein
– GM, Strategic AI & ISV
@ Google Cloud
,
Sam Sebastian
– Vice President, North America Regions
@ Google Cloud
,
Jim Anderson
– Vice President, North America Partner Ecosystem and Channels
@ Google Cloud
,
Chris Sakalosky
– Vice President, Strategic Industries
@ Google Cloud
Join our North America leadership team for a fireside chat on scaling your business with Google Cloud. They will reveal priorities for 2025, how to navigate the AI era, and how industry expertise will play a key role in unlocking and accelerating growth. Discover the latest trends shaping the region, and gain actionable insights to embrace unprecedented opportunities and exceed customer expectations in this transformative age. |
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Accelerating AI In Your Business
2025-03-12 · 08:30
Accelerating AI In Your BusinessJoin us for an exciting event exploring the cutting-edge world of Artificial Intelligence in Business. The event is co-organised by Fliweel.tech, Qoob, Dragon IS, Onyx Data and Pulse Group Media. RSVP HERE - https://www.eventbrite.co.uk/e/accelerating-ai-in-your-business-tickets-1207584781589 This in-person event will take place on Wed, March 12, 2024 at MK:U Innovation Hub, Milton Keynes. Get ready to dive into the future of AI and discover how it is revolutionising the way we do business. During this event, you will have the opportunity to hear from industry experts, thought leaders, and innovators who are at the forefront of AI technology. They will share insights, case studies, and success stories that demonstrate the incredible potential of AI in various business sectors. Gain a deeper understanding of how AI can enhance productivity, streamline processes, and drive innovation in your organisation. Don't miss out on this opportunity to stay ahead of the curve and unlock the power of AI in your business. Register now to secure your spot at Accelerating AI In Your Business! Speakers Andy Paul - Founder & CEO at Fliweel.tech Matthew Rigby-White - CEO at qoob Lionel Naidoo - Managing Director at Dragon IS Leon Gordon - CEO at Onyx Data Who is this event for?This event is for businesses with more than 25 employees and of all sectors. |
Accelerating AI In Your Business
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🌟 Session Overview 🌟 Session Name: Insights into Your Cloud Database: How Storage Engines Actually Work Speaker: Jan Mensch Session Description: In this session, we will dive into the inner workings of cloud storage engines by exploring Hummock, the storage engine behind RisingWave, a streaming database. We will cover how data writes occur in Hummock, focusing on the crucial role of MemTables in managing data before persistence. You will gain an understanding of Log-Structured Merge (LSM) trees and their importance in optimizing both read and write performance. Additionally, we will explore the function of L0 sublevels in accelerating the compaction process. We’ll discuss Sorted String Tables (SSTs), including how they organize data, their versioning, and how this versioning connects to distributed snapshots in streaming systems. Furthermore, we will examine the necessity of compaction and how it represents a trade-off between read and write amplification. By the end of the session, you will gain valuable insights into the mechanics of LSM storage engines and their role in powering streaming databases. 🚀 About Big Data and RPA 2024 🚀 Unlock the future of innovation and automation at Big Data & RPA Conference Europe 2024! 🌟 This unique event brings together the brightest minds in big data, machine learning, AI, and robotic process automation to explore cutting-edge solutions and trends shaping the tech landscape. Perfect for data engineers, analysts, RPA developers, and business leaders, the conference offers dual insights into the power of data-driven strategies and intelligent automation. 🚀 Gain practical knowledge on topics like hyperautomation, AI integration, advanced analytics, and workflow optimization while networking with global experts. Don’t miss this exclusive opportunity to expand your expertise and revolutionize your processes—all from the comfort of your home! 📊🤖✨ 📅 Yearly Conferences: Curious about the evolution of QA? Check out our archive of past Big Data & RPA sessions. Watch the strategies and technologies evolve in our videos! 🚀 🔗 Find Other Years' Videos: 2023 Big Data Conference Europe https://www.youtube.com/playlist?list=PLqYhGsQ9iSEpb_oyAsg67PhpbrkCC59_g 2022 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEryAOjmvdiaXTfjCg5j3HhT 2021 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEqHwbQoWEXEJALFLKVDRXiP 💡 Stay Connected & Updated 💡 Don’t miss out on any updates or upcoming event information from Big Data & RPA Conference Europe. Follow us on our social media channels and visit our website to stay in the loop! 🌐 Website: https://bigdataconference.eu/, https://rpaconference.eu/ 👤 Facebook: https://www.facebook.com/bigdataconf, https://www.facebook.com/rpaeurope/ 🐦 Twitter: @BigDataConfEU, @europe_rpa 🔗 LinkedIn: https://www.linkedin.com/company/73234449/admin/dashboard/, https://www.linkedin.com/company/75464753/admin/dashboard/ 🎥 YouTube: http://www.youtube.com/@DATAMINERLT |
DATA MINER Big Data Europe Conference 2020 |