Microsoft Security Introducing Security Copilot Agents

Event: Security Field Day 13

Appearance: Microsoft Security Presents at Security Field Day 13

Company: Microsoft Security

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Personnel: Nick Goodman

This session explores the evolution and capabilities of Microsoft Security Copilot, focusing on how it’s transforming security operations. Microsoft Security Copilot has evolved to incorporate AI agents, offering a fundamentally different approach to security tasks compared to traditional automation. These agents dynamically plan, reason, and execute tasks, adapting their approach as new information emerges, much like human analysts. This capability has already shown significant benefits, with security teams using Security Copilot reporting incident response times that are approximately 30% faster. The platform is designed to be an ecosystem, with 13 active agents, including six developed by Microsoft and seven by partners, demonstrating a commitment to partner integration and extending AI capabilities across the Microsoft Security Suite.

One notable Microsoft-developed agent is the phishing triage agent, designed to address the overwhelming volume of user-reported phishing incidents. This agent autonomously triages these submissions, analyzing email content, threat intelligence data, and links to determine if an email is genuinely malicious or benign. This frees up human analysts from mundane tasks, allowing them to focus on true threats. The agent learns from human feedback, enabling it to adapt to specific business contexts and improve its accuracy over time. This active learning mechanism, where administrators can provide feedback to the agent, ensures that the AI’s reasoning process is continuously refined, addressing scenarios where the AI might initially misclassify an email due to a lack of organizational-specific knowledge.

Beyond phishing triage, Microsoft Security Copilot includes agents for data loss prevention and insider risk management, which leverage generative AI to classify documents and assist privacy analysts in reviewing alerts. The Conditional Access Agent helps organizations maintain up-to-date security policies by constantly reviewing and suggesting adjustments to conditional access policies, significantly reducing the risk window caused by policy drift. The vulnerability intelligence agent automates the process of reading vulnerability reports, assessing device estates (specifically Windows endpoints), and recommending patching groups in Intune. Lastly, the threat intelligence briefing agent provides organizations with customized reports on cyber threats and vulnerabilities relevant to their specific profile, empowering analysts and organizations that may lack dedicated threat intelligence teams. These agents are designed to integrate seamlessly into existing workflows, enhancing efficiency and enabling security teams to focus on higher-value activities.


Futurum Research Presents Cybersecurity Trends with Fernando Montenegro

Event: Security Field Day 13

Appearance: Futurum Research Presents Cybersecurity Trends at Security Field Day 13

Company: The Futurum Group

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Personnel: Fernando Montenegro

Futurum Research acts as an information broker, connecting technology buyers, sellers, investors, and other stakeholders to provide decision support and insights into the cybersecurity landscape. Their research, led by Fernando Montenegro and with contributions from analysts like Krista Case, encompasses both qualitative and quantitative methods, including a recent survey of over 800 decision-makers across various global markets. This survey, conducted between February and April 2025, focused on understanding organizational changes and perspectives on different cybersecurity fields, with a significant emphasis on senior leadership.

The research identified four major trends shaping cybersecurity in 2025: the pervasive influence of AI, the expanding and increasingly complex attack surface, a significant move towards security platforms, and the evolution of data protection into broader resilience strategies. Organizational trends indicate that cybersecurity is gaining executive visibility, with frequent reporting to senior leadership and a notable increase in security budgets driven by modernization efforts, risk management strategies, and regulatory compliance. When evaluating vendors, product effectiveness and capabilities remain paramount, but total cost of ownership and integration with existing tools are increasingly critical factors. The survey also highlighted challenges in vendor evaluation due to the crowded and noisy cybersecurity marketplace.

Key findings across specific cybersecurity domains reveal several insights. Cloud security incidents and data breaches were the most reported incidents, leading to data loss and operational downtime. In application security, talent shortages and legacy application debt are major challenges, with application development teams often leading security efforts. Cloud security sees stronger ownership by security teams in multi-cloud environments, with a preference for cloud provider-native security solutions. Data security initiatives are increasingly leveraging AI/ML for threat detection and focusing on data security posture management. Endpoint security remains stable, primarily providing telemetry for security operations, while identity management is a “new hotness,” especially concerning non-human identities and rising costs. Risk management and security operations are becoming the central nervous system for modern security, with a focus on improving context derivation and incorporating cloud security into SecOps. Network security emphasizes automation, NDR, and micro-segmentation for zero-trust implementation. Lastly, while optimism about AI’s role in security is high, Futurum stresses the need for education regarding AI’s actual capabilities and limitations in replacing human analysts.


Dell Technologies Infrastructure Security with Steve Kenniston

Event: Security Field Day 13

Appearance: Dell Technologies Presents at Security Field Day 13

Company: Dell Technologies

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Personnel: Adam Miller, Steve Kenniston

Having a secure and resilient infrastructure gives organizations the confidence they need to innovate. Dell helps organizations stay safe and secure, today and into the future, by manifesting a comprehensive security strategy across three core pillars: modern workspace (PCs), modern data center (storage, servers, data protection, networking, HCI), and AI. This holistic approach, known as the Dell Technology Advantage (DTA), integrates security and sustainability across all three components. A dedicated development organization within Dell focuses on creating consistent security capabilities across their entire portfolio, aiming to reduce tool sprawl and provide a unified management experience for customers, including consistent operating systems across appliance solutions for predictable security implementation.

Dell’s infrastructure security strategy aligns with a “reduce attack surface, detect and respond, and recover” framework. To reduce the attack surface, Dell’s servers incorporate features like system lockdown, signed firmware updates, and dynamic USB control, while networking solutions leverage cryptography and secure authentication. For detection and response, features like iDRAC on servers and BIOS live scanning are used to continuously monitor for changes and send notifications upon physical chassis penetration. In terms of recovery, Dell ensures valid recovery points, scans data before recovery, and offers capabilities like scanning snapshots on primary storage for early threat detection and quicker recovery of business-critical data, complementing their data protection solutions with immutable vaults and isolation.

Dell also emphasizes a zero-trust approach, building capabilities into each solution set to support customers in creating zero-trust environments. While they clarified that “certification” by the Department of Defense is better termed “validation,” Dell’s Project Zero architecture adheres to the DOD’s zero-trust guidelines, having undergone testing and validation against their COA3 for on-prem infrastructure. This validation process involved implementing hardware that the DOD could pen-test and validate against various security controls. Additionally, Dell has partnered with CrowdStrike to enhance threat detection within backup environments, identifying over 70 types of attacks and sending actionable intelligence to SIEMs, thus shifting from reactive incident response to proactive detection and providing comprehensive recovery services through their integrated support and engineering teams.


Dell Technologies AI Security with Arun Krishnamoorthy

Event: Security Field Day 13

Appearance: Dell Technologies Presents at Security Field Day 13

Company: Dell Technologies

Video Links:

Personnel: Adam Miller, Arun Krishnamoorthy

AI has become one of the hottest topics in IT. Learn how Dell can help you make sure that as you deploy AI solutions, you do it in a secure manner.

Dell Technologies emphasizes that security is a critical aspect of their journey in accelerating customer outcomes, whether through private and hybrid cloud solutions or advancements in AI. They have established the Dell AI Factory to mass-produce AI solutions at scale with high quality and efficiency, bringing together Dell’s infrastructure, including AI PCs and data center components (compute, storage, GPU-enabled with partners like Nvidia, Intel, and AMD), along with an ecosystem of AI-enabled partners. This comprehensive approach aims to help customers accelerate their AI innovation and achieve faster time to market, recognizing security as a day-zero conversation for successful AI deployment.

Dell highlights the evolving landscape of AI, from traditional AI to generative AI and the emerging agentic AI. With agentic AI, applications will increasingly think for themselves and exercise judgment with minimal human intervention, posing significant security challenges. To address these evolving risks, Dell advocates for a cross-functional architectural approach involving IT, business, data, and security teams from the outset. They stress the importance of organizing and securing data, which fuels AI models, and implementing robust governance. The company is developing an architecture to secure AI deployments, from model training and data organization to runtime environments on-premise, in the cloud, or on AI PCs, acknowledging the shift of AI use cases to the edge.

Dell’s security strategy for AI focuses on making security and resilience an architectural design choice, providing services like strategic advisory, implementation, and continuous threat management. They offer a virtual CISO for AI, data security posture assessment to identify and reduce AI-related risks like data poisoning and prompt injection, and managed security services, including managed detection and response (MDR). Their MDR service provides full-stack visibility, proactively monitoring infrastructure, data protection environments, and cloud/container levels for threats. Dell is also partnering to develop an “AI proxy” or “AI firewall” for deep prompt-level inspection, compliance violation assessment, and malicious code detection, and offers penetration testing against OWASP Top 10 AI vulnerabilities, emphasizing a proactive and collaborative approach to securing AI implementations.


Dell Technologies Endpoint Security

Event: Security Field Day 13

Appearance: Dell Technologies Presents at Security Field Day 13

Company: Dell Technologies

Video Links:

Personnel: Adam Miller, Justin Vogt

When it comes to security at the endpoint, we will discuss how Dell helps to keep your organization safe.

In this session, Dell Technologies presented a deep dive into their commercial PC endpoint security capabilities. Justin Vogt and Adam Miller outlined how Dell’s approach spans secure manufacturing, below-the-OS threat detection, hardware-based credential protection, and direct integrations with industry-leading security tools. Their security strategy is rooted in building a trusted platform from the supply chain up, with controls like Dell’s SafeBIOS for firmware verification, SafeID for dedicated credential storage, and tamper-evident delivery methods. These security layers are automatically embedded in Dell commercial devices like Dell Pro and Dell Pro Max, which are built with telemetry and validation mechanisms that detect firmware tampering and alert security teams proactively.

Dell also emphasized integration with silicon partners, especially Intel, to gain visibility into memory at the hardware level, bypassing potentially compromised operating systems. Unique capabilities such as off-host firmware verification and BIOS indicators of attack give organizations the ability to detect abnormal behavior even before standard security tools are active. Beyond detection, Dell helps customers with incident response by enabling forensic data capture and supporting secure recovery. These capabilities are made actionable through direct integrations with platforms like Microsoft Intune, CrowdStrike, and Absolute, so customers can manage and respond to threats using tools they already know. All this is offered without additional cost, and Dell provides both a hardware and software bill of materials to ensure transparency and trust in every device.

Complementing their built-in security, Dell offers optional managed services to help customers who may not have mature security operations. Their customer security operations center can monitor hardware-level data and support incident response and recovery–even on non-Dell environments. With a focus on reducing mean time to detect and respond, Dell positions itself not only as a hardware vendor but as a security partner. The presentation highlighted Dell’s ethos of proactive defense, transparency, and support, driven by both product capabilities and service expertise. Customers can rely on Dell for end-to-end security–from foundational hardware assurance to advanced telemetry and threat remediation.


Dell Technologies Security Strategy Overview

Event: Security Field Day 13

Appearance: Dell Technologies Presents at Security Field Day 13

Company: Dell Technologies

Video Links:

Personnel: Adam Miller, Sameer Shah, Steve Kenniston

This session will cover Dell’s overall strategy for cybersecurity including reducing the attack surface, detecting and respond to cyber threats, and recovering from a cyberattack.

In this presentation at Security Field Day 13, Dell Technologies provided a comprehensive overview of their cybersecurity strategy, emphasizing the concept of “advanced cybersecurity maturity.” The speakers explained that Dell aims to help customers progress in their cybersecurity posture by embedding security from the ground up—starting with the supply chain and extending through endpoints, infrastructure, and services. With the rise of AI, the attack surface has expanded, and bad actors have gained access to more sophisticated tools. In response, Dell focuses on three strategic pillars: reducing the attack surface, detecting and responding to threats, and ensuring rapid recovery. Their approach includes building secure hardware (claiming the most secure commercial and AI PCs), utilizing industry-vetted security partnerships, and providing services that align with the Zero Trust model.

Dell’s reduction of the attack surface involves enforcing strong cyber hygiene, emphasizing practices such as regular patching, encryption, multi-factor authentication, and network segmentation. The company views cybersecurity as not only technological but procedural, with detection strategies that incorporate AI/ML-enhanced XDR tools and, where possible, managed detection and response (MDR) services. Their hardware is designed with security baked in, including features like firmware verification and behavioral detection at the BIOS level. They also stress the importance of monitoring, both with built-in capabilities and via partner integrations. Dell aims to give customers not only preventative tools but also detection systems that assume eventual breach, shifting focus toward resilience.

Recovery, as Dell sees it, is the ultimate goal and involves both technology and process readiness. Their solutions include air-gapped cyber vaults and services that support incident response planning, communications, and business continuity. For Zero Trust, Dell supports two paths: an incremental uplift approach for customers with existing investments, and Fort Zero, a pre-certified private cloud solution aligned with the U.S. Department of Defense’s Zero Trust architecture. Fort Zero integrates hardware and software from vetted partners and is delivered as a turnkey system. Dell also supports brownfield environments through consulting services and maturity-based architecture planning. Overall, the presentation framed cybersecurity not as a static goal but as a continual process of improvement, which is rooted in practical frameworks, backed by technology, and supported by Dell’s ecosystem of services and partners.


Driving AI-Powered Analytics with Mike Potter of Qlik

Event: Tech Field Day Experience at Qlik Connect 2025

Appearance: Tech Talks at Qlik Connect 2025

Company: Qlik

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Personnel: Mike Potter, Stephen Foskett

In this interview at Tech Field Day during Qlik Connect 2025, Stephen Foskett interviews Mike Potter, Chief Technology Officer at Qlik, discussing the company’s latest advancements in integrating AI into its analytics platform. Potter emphasizes that Qlik’s vision is to manage the entire data lifecycle—from ingestion and transformation to analytics and actionable insights. Qlik’s introduction of the new agentic framework and enhancements such as intelligent data cataloging and business glossary automation are designed to help users turn complex, unstructured data into structured insights. The goal is to shift the focus from technical hurdles to business value by automating routine tasks and creating a more governed and scalable data environment.

A major challenge Potter highlights is that while organizations often have the intelligence they need, they struggle with executing on that information in real-time and at scale. He explains how Qlik’s AI-driven tools—such as Qlik Answers, which allows users to query data in natural language—are democratizing access to analytics. By equipping non-technical users with capabilities traditionally limited to data specialists, Qlik transforms decision-making across entire enterprises. These tools not only facilitate quicker insights but also align with enterprise needs for reliable, referential data by blending deterministic analytics with generative AI to strengthen context and relevance.

Potter also reframes the ongoing debate about cloud adoption, pointing out that most organizations are no longer deciding if they will move to the cloud—but rather how fast they can get there without sacrificing their existing investments. Qlik’s partnership-driven ecosystem, support for open standards like Apache Iceberg, and recent acquisitions further enable seamless cloud migration and integration with both cloud-native and legacy systems. With flexible architecture and strategic alliances with providers like AWS, Qlik ensures customers can innovate on their terms while maintaining agility and enterprise-grade governance.


Olawale Oladehin on Advancing Enterprise AI Adoption with AWS and Qlik

Event: Tech Field Day Experience at Qlik Connect 2025

Appearance: Tech Talks at Qlik Connect 2025

Company: AWS, Qlik

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Personnel: Stephen Foskett, Wale Oladehin

At Qlik Connect 2025, Olawale “Wale” Oladehin of AWS reflected on the progress made since the AWS-Qlik collaboration was initiated, emphasizing shared goals in advancing enterprise AI adoption and aligning around open standards, scalability, and governance. Wale highlighted how joint customers benefit from Qlik’s strength in data integration, movement, and quality, paired with AWS’s robust infrastructure and AI capabilities. The partnership ensures enterprises can easily scale AI workloads with reliability while leveraging both platforms for better data-driven insights. One of the key developments they discussed was the shared commitment to open frameworks like Apache Iceberg, which boost interoperability and reduce vendor lock-in—a vital factor for modern analytics and AI workloads.

Wale also explored how AWS and Qlik are delivering customer confidence in generative AI use cases through tools like Amazon Bedrock. These technologies foster responsible AI usage by incorporating features like agent orchestration, LLM guardrails, and governance layers to help prevent misinformation such as hallucinations. The interview underscored how customers, particularly in regulated industries like finance and pharmaceuticals, are rapidly adopting gen AI due to already having solid foundations in data security and compliance. Wale emphasized that AWS builds backward from customers’ needs, ensuring they apply AI solutions appropriate to their business goals, whether building custom models, implementing agents, or utilizing fully managed services for immediate productivity boosts.

The discussion also touched on broader industry shifts, notably the normalization of cloud infrastructure. Wale commented that today’s enterprises not only trust the cloud but view it as a default platform, expecting seamless SaaS and infrastructure-level services. This shift is emphasized through AWS and Qlik’s integration strategies, delivering flexibility through cloud-native but hybrid-compatible solutions. At his Tech Field Day presentation, Wale elaborated on these themes, showing demos and discussing the practical application of AI on AWS for Qlik users.


Agentic AI and the Future of Science — A Conversation with Michael Bronstein and Nick Magnusson at Qlik Connect 2025

Event: Tech Field Day Experience at Qlik Connect 2025

Appearance: Tech Talks at Qlik Connect 2025

Company: Qlik

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Personnel: Michael Bronstein, Nick Magnuson, Stephen Foskett

At Qlik Connect 2025, Stephen Foskett interviewed Michael Bronstein, DeepMind Professor of Artificial Intelligence at the University of Oxford, and Nick Magnuson, Head of AI at Qlik, explored the transformative potential of agentic AI in science and enterprise. Bronstein highlighted how agentic AI may represent a seismic shift in the scientific method, moving beyond traditional roles in simulation and prediction to now participating in creative hypothesis generation—a realm historically reserved for human ingenuity. This evolution positions AI as not just a tool but a fellow innovator, potentially capable of reaching milestones like Nobel Prize-worthy contributions. While the impact in experimental sciences faces challenges due to the messiness of real-world labs, fields like mathematics and software development—where elements are inherently digital—might more quickly benefit from AI’s capabilities.

Magnuson elaborated on Qlik’s role in enabling agentic AI across industries through scalable analytics and data infrastructure. Qlik is actively working to address the complexity of querying massive data lakes, especially as AI systems demand broader, multimodal, and high-velocity datasets. This adaptation aligns with the shift towards machine-centric data generation and processing, emphasizing how data and AI models must evolve in tandem. Magnuson also noted that synthetic data is increasingly prevalent and necessary for training AI agents capable of exploring previously unapproachable scenarios at scale. Nonetheless, challenges connected with the trustworthiness and verification of such data remain critical.

The interview concluded with a discussion about the deeper implications of agentic AI creating new paradigms in both science and enterprise. Bronstein suggested that scientific data collection itself may need to evolve, moving towards formats interpretable by AI but potentially opaque to humans. Meanwhile, Qlik’s innovations aim to support this transition by developing infrastructure capable of handling such complex, varied, and massive-scale data input. As the use of agents grows, particularly in autonomous exploration and decision-making, enterprises must not only consider technical capabilities and applications but also ethical and regulatory implications. These developments advance the broader conversation about co-evolution between AI and scientific inquiry and reaffirm the necessity of continued, rigorous interdisciplinary collaboration.


Advancing Data Integration and Analytics with Sam Pierson and Ori Rafael of Qlik

Event: Tech Field Day Experience at Qlik Connect 2025

Appearance: Tech Talks at Qlik Connect 2025

Company: Qlik

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Personnel: Ori Rafael, Sam Pierson, Stephen Foskett

At Tech Field Day during Qlik Connect 2025, Stephen Foskett interviewed Sam Pierson, SVP of R&D for the Data Business Unit at Qlik, and Ori Rafael, former CEO and co-founder of Upsolver and now Senior Director of Engineering at Qlik, about the major announcement of Qlik’s Open Lakehouse. This new offering aims to bridge the gap between unstructured data lakes and the highly governed, structured world of data warehouses. Built on open standards like Apache Iceberg, the Open Lakehouse allows Qlik to deliver scalable, performant, and cost-efficient data management that makes data easier to access, transform, and analyze. As the industry sees a shift from mere data storage to true data usability across diverse environments, Qlik sets itself apart by embedding the openness and flexibility that enterprises now demand.

Ori provided valuable insight into how Upsolver’s technology is enhancing Qlik’s data ecosystem. Originally created to simplify Big Data workloads, Upsolver built a declarative, low-engineering approach to ingesting and managing massive datasets. With the integration into Qlik, the capabilities of Upsolver now power the Open Lakehouse, turning what was typically a data engineering bottleneck into a user-friendly and performant experience. Ori emphasized how Upsolver solves the “last mile” challenge in data lakes — turning raw, complex data into consumable assets without the overhead typically associated with Hadoop or similar systems. This evolution allows smaller datasets to be managed with the same agility, leading to a universal platform for beginners and advanced users alike.

Sam highlighted how Upsolver’s ingestion performance and native integration with technologies like Apache Iceberg align strongly with Qlik’s goals and existing offerings, such as the Qlik Talend Cloud. The acquisition has been particularly beneficial in scaling their data integration efforts, improving connectors—especially for more complex systems like SAP and mainframes—and supporting seamless interoperability with key cloud partners like AWS. This alignment of vision and strategy between the two companies has rapidly accelerated product development, with early access programs already in motion. Combining Qlik’s extensive analytics and AI tools with Upsolver’s robust ingestion engine offers a compelling package for customers seeking flexible, open, and high-performance data solutions.


Responsible and Inclusive AI Innovation in Analytics with Mary Kern and Rumman Chowdhury

Event: Tech Field Day Experience at Qlik Connect 2025

Appearance: Tech Talks at Qlik Connect 2025

Company: Qlik

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Personnel: Mary Kern, Rumman Chowdhury, Stephen Foskett

In this interview from Tech Field Day Experience at Qlik Connect 2025, Stephen Foskett interviews Mary Kern, VP of Analytics Go-To-Market at Qlik, and Rumman Chowdhury, CEO of Humane Intelligence and a Qlik AI Council member, about the state of AI in today’s analytics landscape. They discuss the paradoxes of 2025, where the rise of powerful centralized AI platforms coincides with a growing open-source movement, enabling wider global access. Rumman highlights the democratizing force of open-source AI, underscoring how inclusive engagement and grassroots participation are essential for future innovation. Mary adds that while AI promises efficiency and transformation, enterprises continue to grapple with responsible implementation and trust in these evolving technologies.

As both leaders emphasize, AI’s impact is most meaningful when it enhances accessibility, enabling users across varying skill levels and geographies to engage with analytics tools more intuitively. Language models acting as user interfaces make complex tools more approachable, especially for users without technical backgrounds or those with disabilities. By leveraging natural language processing and multi-language support, AI can elevate users’ performance and confidence in decision-making, making business intelligence more powerful and human-centric across cultures. Mary notes that the future of analytics isn’t about AI replacing humans but about enabling broader, better performance powered by data-driven insights.

The conversation also delves into the cultural nuances of AI deployment globally. Rumman raises concerns about bias in AI models when applied across different societies and languages. She explains the importance of culturally aware AI, citing her organization’s joint work with ASEAN to rigorously test models for multicultural bias. Mary reflects on how Qlik builds diverse perspectives into their development process, ensuring AI models are not only useful but trustworthy and aligned with enterprise needs. This intentional approach—with baked-in trust, bias monitoring, and global sensitivity—demonstrates Qlik’s commitment to responsible AI integration in analytics at scale.


Qlik Connect 2025 Delegate Roundtable on Agentic AI

Event: Tech Field Day Experience at Qlik Connect 2025

Appearance: Tech Field Day Delegate Roundtable at Qlik Connect 2025

Company: Qlik

Video Links:

Personnel: Stephen Foskett

The Tech Field Day Delegate Roundtable at Qlik Connect 2025 brought together key thought leaders to discuss the rapid evolution and practical implications of agentic AI in the enterprise data ecosystem. With agentic AI emerging as a prominent theme for this year, delegates evaluated its current state, its impact on organizations, and Qlik’s approach to integrating AI-centric workflows into their platform.

Throughout the roundtable, panelists acknowledged that while agentic AI—AI-driven workflows composed of autonomous or semi-autonomous agents—has gained significant marketing traction, its implementation in production environments remains aspirational for most enterprises. They praised Qlik for its data-first approach, recognizing the company’s efforts to merge structured and unstructured data as a foundational step toward enabling more intelligent AI-based decisions. However, skepticism remained about the readiness of many organizations to deploy such systems, given the ongoing challenges with data quality, observability, and trustworthiness in AI outputs. The importance of foundational data governance and automation was emphasized, with clarity needed between traditional scripting, automation, and true AI-enabled agentic systems.

Delegates discussed the philosophical and technical nuances of what qualifies as agentic, highlighting that many current use cases are partially agentic at best, often relying on conventional automation or rules-based logic augmented by AI components. They advocated for a pragmatic view: while agentic AI is real and being pursued, the industrial-scale implementation still hinges on getting core data practices right: cleaning and organizing legacy systems, ensuring output trust, and creating frameworks that allow controlled evolution of AI agents. The group agreed that Qlik is moving the ecosystem in the right direction but stressed that success will depend on keeping expectations grounded and distinguishing aspirational demos from deployable solutions.


Tech Field Day Experience at Qlik Closing Summary

Event: Tech Field Day Experience at Qlik Connect 2025

Appearance: Qlik Presents at TFDx Qlik Connect 2025

Company: Qlik

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Personnel: Josh Good

In the closing session of the Tech Field Day Experience at Qlik Connect 2025, Josh Good recapped key highlights from the event, emphasizing Qlik’s strong partnership with AWS, which supports robust cloud adoption and integration. He detailed the company’s AI-driven capabilities—including Qlik Answers, Qlik Predict, and agentic AI functions—highlighting how these tools enhance analytics and usability. Josh also showcased Qlik’s embeddable technology and advances such as the Open Lakehouse architecture and new AI-ready features like multivariate time series analysis and AI-assisted table creation. He underscored Qlik’s commitment to supporting clients’ transitions to the cloud while maintaining flexibility based on individual needs.


Qlik Open Lakehouse Deep Dive

Event: Tech Field Day Experience at Qlik Connect 2025

Appearance: Qlik Presents at TFDx Qlik Connect 2025

Company: Qlik

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Personnel: Antoine Richard, Ori Rafael, Vijay Raja

In this session at Tech Field Day Experience at Qlik Connect 2025, Qlik unveiled and explored its new Qlik Open Lakehouse initiative, an outcome of the company’s acquisition of Upsolver. The presentation focused on the growing market adoption of Apache Iceberg, an open table format for data lakes, driven by its advantages in cost savings and interoperability. Ori Rafael highlighted the transition from traditional, tightly coupled data warehouses to decoupled data lakehouses using Iceberg. This shift enables enterprises to eliminate redundant warehouse storage costs by directly writing to cost-efficient object storage like Amazon S3. Furthermore, Iceberg allows customers to decouple compute from storage and use multiple analytics engines (like Snowflake for BI or Databricks for AI) on a unified data layer, enabling a truly open and flexible data architecture.

Qlik’s acquisition of Upsolver has enhanced its capabilities to deliver an enterprise-grade, high-performance lakehouse solution. The Qlik Open Lakehouse, now integrated into Qlik’s Talend Cloud platform, provides high-throughput ingestion, real-time processing, and automatic optimization of Iceberg tables. This includes features such as adaptive file compaction, dynamic partitioning, and efficient snapshot cleanup to keep storage lean and query performance high. Ori shared benchmarks demonstrating that Iceberg tables managed by Upsolver could achieve query performance nearly on par with native Snowflake storage, while offering as much as 2x improvement in storage efficiency over other Iceberg implementations. This level of performance addresses previous shortcomings of Hadoop-based data lakes and provides a practical, streamlined experience that doesn’t require specialized big data engineering expertise.

Antoine Richard and Vijay Raja elaborated on Qlik Open Lakehouse’s integration into Qlik Talend Cloud, detailing its core capabilities that support ingestion from hundreds of sources via batch or CDC, optimizer services tailored for Iceberg, and seamless mirroring into Snowflake without duplicating data. They outlined support for Iceberg catalogs like AWS Glue, Polaris, and Snowflake Open Catalog, enhancing query engine compatibility across platforms like Spark, Trino, and Dremio. The product roadmap includes enhancements like streaming ingestion, support for additional cloud providers, and advanced transformation tooling, reinforcing Qlik’s mission to provide an end-to-end data integration platform. A recorded demo concluded the session, illustrating how users can build data pipelines into Iceberg via Qlik Talend Cloud, view data in Athena or Snowflake, and perform seamless transformations, all while maintaining a familiar UI and minimizing the need for warehouse compute resources.


Qlik Embedded Analytics and AI Deep Dive

Event: Tech Field Day Experience at Qlik Connect 2025

Appearance: Qlik Presents at TFDx Qlik Connect 2025

Company: Qlik

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Personnel: Dave Channon, Luciane Ellis

In their session at Tech Field Day Experience during Qlik Connect 2025, Luciane Ellis and Dave Channon explored the transformative impact of embedded analytics and AI on business applications. Emphasizing the increasing demand for real-time insights directly within workflows, the presenters highlighted how businesses are evolving past isolated dashboards to meet the expectations of both technical and non-technical users. The focus is now on integrating intelligence seamlessly into everyday tools like CRM or supply chain platforms, allowing users to get instant, context-aware insights without shifting applications. These embedded capabilities are proving valuable for independent software vendors (ISVs), who can now offer AI-augmented features such as predictive analytics and natural language interaction, translating into operational efficiencies and premium offerings for end customers.

As part of this transformation, Qlik has developed a suite of technology to support modern embedded analytics. Their Qlik Embed framework provides lightweight, cookie-free web integration and supports major frontend technologies, allowing applications to scale flexibly across multi-tenant SaaS architectures. Features like generative and predictive AI are natively integrated, enabling ISVs to deliver intelligent, hands-off experiences that vary based on user roles and access levels. These capabilities are not just limited to desktop environments but are essential for mobile use cases, such as logistics or retail operations, where quick, in-context insights are crucial. Moreover, Qlik emphasizes governance, security, and real-time user personalization, which are critical for enterprises and ISVs looking to deploy scalable, secure solutions.

To demonstrate the power and scalability of Qlik’s embedded platform, Dave Channon showcased a fictional ISV demo, Smart Chain. This end-to-end demo illustrated how quickly an isolated customer tenant can be spun up with full analytics, self-service dashboards, and AI-driven experiences wrapped within a single application workflow. The process included automated provisioning of data, users, apps, and assistants—all using Qlik’s rich API ecosystem and automation tools. The embedded analytics included customizable views, predictive insights, report generation, and visual interactivity—all accessible to users of varying roles and technical expertise. This approach, which combines centralized ISV-driven models with end-user-specific tuning, demonstrates Qlik’s flexibility and strength in delivering intelligent, user-centric, and scalable analytics solutions.


Qlik AI Strategy Overview and Agentic AI Deep Dive

Event: Tech Field Day Experience at Qlik Connect 2025

Appearance: Qlik Presents at TFDx Qlik Connect 2025

Company: Qlik

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Personnel: Kyle Jourdan, Nick Magnuson

In this presentation from Tech Field Day Experience at Qlik Connect 2025, Qlik’s Nick Magnuson and Kyle Jourdan discuss Qlik’s strategic approach to artificial intelligence, focusing on integrating AI to solve real business problems with accuracy and trust. They explore how Qlik’s AI approach encompasses traditional predictive analytics, generative AI, and newer agentic AI paradigms—all within a unified, enterprise-grade ecosystem. The presentation emphasizes the evolution of Qlik’s AI capabilities, including the integration of structured and unstructured data within Qlik Answers, the expansion into autonomous agent actions, and the critical importance of customer-centric AI deployment.

In the session, Magnuson articulates Qlik’s AI philosophy, explaining how a pragmatic, use-case-first mindset underpins their strategy. Rather than blindly adopting large language models (LLMs) or generative AI for the sake of innovation, Qlik promotes applying the right form of AI—whether predictive, generative, or agentic—based on the specific business need. He shares concrete examples such as healthcare applications using predictive models to reduce patient no-shows and recover lost revenue, demonstrating how Qlik’s platform, bolstered by its acquisition of BigSquid and the resulting Qlik Predict, has delivered over a billion predictions. With Qlik Answers, initially a generative AI tool for unstructured data, now embracing agentic AI concepts, the platform can act autonomously on structured data, bridging the gap between conversational insights and actionable business operations.

The presentation continues with Jourdan providing a deep dive into the agentic evolution of Qlik Answers. He demonstrates how the system can handle natural queries, pull structured and unstructured data, generate visualizations, and take contextual actions such as sending messages or updating databases—all through a codeless, drag-and-drop interface. Advanced features such as explainability, AI trust scores, and the handling of lifecycle concerns like data governance and versioning are also discussed, emphasizing Qlik’s commitment to enterprise-grade standards. Moreover, Qlik’s neutral stance as an independent vendor provides flexibility for integration and multi-platform support, distinguishing it from hyperscalers with closed ecosystems. In closing, the session showcases upcoming tools like native time-series modeling and further automation integrations, reinforcing Qlik’s vision to empower users across technical skill levels to leverage the full power of AI responsibly and effectively.


AWS and Qlik Strategic Collaboration Overview

Event: Tech Field Day Experience at Qlik Connect 2025

Appearance: Qlik Presents at TFDx Qlik Connect 2025

Company: AWS, Qlik

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Personnel: Piyush Bothra, Wale Oladehin

In this presentation at the Tech Field Day Experience during Qlik Connect 2025, AWS and Qlik elaborated on their long-standing partnership and how it has evolved to support modern data workflows and advanced analytics. They emphasized their decade-long collaboration, focusing on helping customers drive digital transformation through scalable cloud infrastructure and sophisticated data analytics. Joint customer success stories were shared to illustrate how enterprises, such as Vanguard, are leveraging AWS and Qlik to modernize critical systems — including SAP and mainframes — to enable near real-time data insights and enhanced operational efficiency.

The session highlighted the integration between AWS’s comprehensive infrastructure and Qlik’s advanced data analytics capabilities, particularly emphasizing Qlik Answers — a generative AI-powered data assistant. Powered by AWS services like Amazon SageMaker and Amazon Bedrock, Qlik Answers enables users to interact with their data through contextual and explainable AI-generated responses. The system architecture involves embedding user queries into vector databases using models like Cohere, with re-ranking and inference handled by Bedrock leveraging Anthropic’s Claude model. This ecosystem supports both structured and unstructured data access while maintaining transparency and traceability of responses, ensuring enterprise-grade security, privacy, and explainability.

Throughout the discussion, the presenters underscored the importance of flexibility, managed services, and shared responsibility in building secure AI applications. AWS’s three-tiered generative AI stack — infrastructure, foundational models, and managed APIs — provides customers and ISVs like Qlik with the tools and services needed to rapidly innovate while maintaining control over customization and data governance. Managed services are increasingly preferred by businesses aiming for faster adoption without sacrificing compliance, security, or accuracy. With AWS deeply committed to privacy, sovereignty, and model performance, and Qlik offering data integration from legacy systems to modern AI applications, this partnership provides a highly scalable and secure ecosystem for advanced analytics and decision-making.


Qlik Connect 2025 Introduction

Event: Tech Field Day Experience at Qlik Connect 2025

Appearance: Qlik Presents at TFDx Qlik Connect 2025

Company: Qlik

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Personnel: Josh Good

At Qlik Connect 2025, Josh Good opened the event by laying out Qlik’s strategic vision and market aspirations. He focused on how Qlik is actively shaping its future, particularly over multi-year horizons, through a combination of AI, analytics, and market positioning. The company aims not just to solve traditional business challenges but also to impact societal issues such as poverty and logistics with its data-centric technologies. Josh highlighted recent achievements including the launch of Qlik Answers and Qlik Cloud, the global AI Reality Tour, and the acquisition of Upsolver, all of which underscore Qlik’s commitment to innovation and broadening their reach.

Josh also explored the market trends driving Qlik’s roadmap, particularly around the emergence of AI agents, the discernment between AI hype and applied value, and the importance of authenticity in data. He discussed how Qlik plans to integrate AI agents more fully into their product suite to allow for faster action from analytics and lower the effort required by users to extract value. Their new capacity-based pricing model reflects a more flexible and comprehensive user experience, enabling organizations to derive more from the platform. Furthermore, Qlik is positioning itself as an end-to-end solution provider by uniting its acquired technologies (like Talend and Attunity) into a seamless ecosystem that appeals to users looking to simplify their modern data stack.

Looking ahead, Qlik is doubling down on agentic AI and exploring new frameworks for enabling fast, actionable insights. Josh emphasized a future with multi-agent architectures and AI readiness, where agents handle core workloads and fluidly cooperate, possibly across ecosystems via protocols like MCP or A2A. The strategy also includes seamless embedding of AI, both predictive and generative, into Qlik’s products so users experience AI’s benefits without needing to understand the technicalities. Ultimately, Qlik’s platform flexibility, partnerships (such as with AWS), robust ecosystem, and investment-backed growth signal a confident path toward becoming a foundational AI-powered analytics provider for tomorrow’s digital enterprises.


Futurum Research: The State of AI PCs

Event: Mobility Field Day 13

Appearance: Futurum Presents AI Devices Research at Mobility Field Day 13

Company: The Futurum Group

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Personnel: Ron Westfall

This presentation features recent findings from an in-depth study by Futurum Research on AI PCs and the results that point to a shift in the enterprise end user compute space. AI PCs contain dedicated neural processing units (NPUs) that help with GenAI, machine learning, and deep learning workloads. AI PCs use NPUs and GPUs together.

The study surveyed 852 enterprise decision makers globally. It found that AI PCs in the laptop form factor lead the market with nearly 70% market share. AI PCs enable hybrid AI with both local and cloud processing options. They reduce the dependency on cloud, especially for highly secure workloads. One of the biggest drivers for AI PC adoption is the pending end-of-life for Windows 10, with users looking to move to Windows 11 on new supported hardware that includes AI PC features.

AI PCs are key edge devices that provide high performance Wi-Fi 7 chipsets, low latency and great power efficiency, as well as enhanced security to prevent user exposure. There is also a growing inclusion of 5G-enabled connectivity on AI PC laptops, especially in sectors where security is paramount.

The presentation wraps with with a discussion of where AI PC technology is headed, such as the rise of agents AI, increased thermal management, and even the future of self diagnosing, self healing computers.


Juniper Location & Analytics: UWB, Dual BLE, PMA-Meeting/Security insights Marvis Client

Event: Mobility Field Day 13

Appearance: Juniper Networks Presents at Mobility Field Day 13

Company: Juniper Networks

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Personnel: Anilash Azeez

Explore the advancements in location services driven by Wi-Fi 7 technology, including ultra-wideband and dual BLE radios that improve indoor positioning. Discover various applications such as asset visibility and user engagement, and learn how machine learning enhances tracking and safety. The importance of contextual awareness in marketing and auto placement technology for accuracy is highlighted, along with telemetry data for IT management. Customer success stories showcase real-world benefits.


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