Sponsor Exhibit Theater Agenda

Two of the hottest new data technology categories in the last 12 months have been Data Observability and Agentic Data Management. Join this session to see how Acceldata has unified both concepts to deliver the next generation data management platform that’s powering Enterprise Data Management for G2000 companies.

Ramon Chen is the Chief Product Officer at Acceldata. He brings more than three decades of enterprise product and marketing leadership experience. Chen is a widely read blogger and speaker on the topics of AI, Data Observability, Master Data Management & Data Quality. A former software engineer, he has spent his entire career developing and marketing enterprise software, helping create market categories that solve enterprise business challenges. Prior to joining Acceldata, Chen served as CPO and CMO for Reltio, the leading cloud MDM platform, and held senior leadership positions at Veeva Systems, RainStor, Siperian, GoldenGate Software and ActivTrak. He graduated from the University of Essex with a bachelor’s degree in computer science, specializing in AI.

Come join the Microsoft Purview team for a deep dive into the Unified Catalog. Learn how this enterprise catalog simplifies data discovery across multiple clouds and data platforms, enables businesses to curate a catalog that reflects your own organization and provides health management tools to ensure the data in your data estate is of high quality, Whether you’re a business leader, data steward, or IT professional, this session will showcase valuable insights into data governance and touch upon topics such as data products, CDEs, Governance domains, data quality, access management, and data lineage.

Kevin is a Senior Product Manager on the Microsoft Purview Data Governance Customer Experience Engineering (CxE) Team, where he provides best practices and deployment guidance to help customers quickly onboard Microsoft Purview Data Governance. Kevin has been working at Microsoft since 2011 in various roles, including senior support escalation engineer on the Microsoft CSS Security team and as a senior premier field engineer, focusing on Microsoft security and information protection. Kevin has spoken at many technical conferences, including RSAC, Microsoft Ignite, Microsoft MVP Summits, and the Microsoft Security Engineering Advisory Council. Prior to starting at Microsoft, he worked for IBM as a Microsoft support manager and spent eight years as an information systems technician first class petty officer while on active duty in the United States Navy. Kevin holds a Bachelor of Science in Business Management, a post-graduate certificate in AI and Machine Learning for Business Applications and holds many certifications including CISSP and GCIH.

The next-gen Amazon SageMaker, the center for all your data, analytics, and AI, has data and AI governance built-in to streamline discovery, understanding, secure sharing, and collaboration across your data ecosystem. Teams securely access and discover approved data and models through AI-powered semantic search and publish and subscribe workflows within the SageMaker catalog and lakehouse architecture. Enhanced with data quality monitoring, sensitive data detection, and comprehensive ML lineage tracking, Amazon SageMaker gets you from raw data to trusted data and finally to trusted AI.

Raghavarao Sodabathina is a Principal Solutions Architect at AWS, focusing on data analytics, AI/ML, and cloud security. He engages with customers to create innovative solutions that address customer business problems and accelerate the adoption of AWS services. In his spare time, Raghavarao enjoys spending time with his family, reading books, and watching movies.

Taking generative AI solutions to production relies heavily on preparing and optimizing enterprise data for applications. This discussion outlines the essential requirements and techniques for making enterprise data “AI ready.” It details the core activities for transforming fragmented, low-quality, and siloed data into a governed, high-value asset that fuels AI-driven insights and automation. Key areas of focus include enhancing data quality, integrating structured and unstructured data, enabling real-time access, and implementing metadata, governance, and semantic enrichment.

John is the Vice President of Data Modernization at Thoughtworks, where he brings over 18 years of experience in diverse data and analytics capacities.. His extensive career spans more than three decades, focusing on the development of crucial software applications and business intelligence solutions worldwide. Before his tenure at Thoughtworks,, John held architect and project management positions at Towers Watson, Deloitte Consulting, and Hyperion Software. In 2012, he led the launch of Thoughtworks’ data analytics practice in North America. A well-known proponent of modern data engineering techniques, John frequently contributes to Thoughtworks’ insights on subjects like data mesh and data governance.

In an era where data is the new economy, PiLog Data Quality & Governance Suite redefines enterprise data management by fusing AI-driven intelligence with a quantum-inspired vision for transformation. Built on lean management principles and ISO standards, the suite delivers a comprehensive framework for mastering data across ERP, Operations, Service and CMMS ecosystems. The Quantum Vision represents PiLog’s strategic leap into next-generation data governance, where real-time insights, predictive analytics, and semantic enrichment converge to enable autonomous decision-making and operational excellence. The suite includes modular capabilities for Data Governance, Cleansing, Classification, Enrichment, Migration, and SAP MDG Add-ons, all seamlessly integrated with S/4HANA via secured APIs and cloud-native architecture. This session will explore how PiLog’s AI-powered suite accelerates digital transformation, enhances compliance, and supports sustainability goals across asset-centric industries. Attendees will gain insights into the suite’s AI Agents, integration touchpoints, and responsible AI features, as validated through SAP’s Premium Certification process.

Salomon has 45 years of cross-industry experience around the globe, he is also on the ISO 8000 committee as part of ISO TC184/SC4 contributing for the development of Data standards. He holds Doctor of Philosophy in System Engineering and Logistic design. Dr Salomon de Jager completed his Hons. B-Eng. degree (Mech. Ind.) in 1978 at the University of Stellenbosch South Africa. During his 2 year National Service in the South African Army he became an officer, contributed to Weapon Systems Development, Logistic Support System Design and obtained his M Eng. (Ind.) degree in 1981 at the University of Pretoria South Africa. The thesis was done in the field of systems simulation of the man-machine interfaces on the helmet visor of the pilot of an attack helicopter. National service was followed by six years of national service camps. During these camps Salomon was utilized on the development of models for the establishment of Logistic Data Analysis and data records required for the establishment of Integrated Logistic Software Systems in the Department of Defense. Since 1978 Dr Salomon worked as Professional Engineer for Iron and Steel Corporation SA for six years and was involved in the design and optimization of asset and inventory management systems. In 1984 Salomon established a consultancy practice which merged into a software systems development house Paradigm Systems Technology. The company successfully developed and implemented the integrated asset and logistics management for the South African Air Force and Navy. Successful Asset and Maintenance Management systems was also developed and implemented for the Steel, Utilities, Mining, Nuclear, Telecom, Aviation and Petrochemical Industries. This elaborated experience was used to complete his PhD in System Engineering and Logistic design in 1993 at Witwatersrand University Johannesburg. The thesis was on System Engineering and integrated acquisition processes in nuclear enrichment equipment. Since 1985 Salomon was the head of the functional design team of Paradigm Systems. In 1994 the UK Royal Air Force chose the Paradigm Software Solution as the integrated logistic solution for the UK Royal Air Force. British Aerospace bought the Paradigm Company and Dr Salomon initiated a management buyout for the Industrial Division of Paradigm which became Pilog in 1995. Pilog business exteded into catalogue and data content solutions and this led to the establishment of Pilog Data in 1999. It was Dr Salomon’s vision that data and data investments would become the assets of the future and therefore Pilog Data was established to focus on data, schemas, standards and e- solutions. Dr Salomon participated in ISO TC184/SC4 since 2006 and initiated a South African mirror committee, SABS TC184 within the South African Bureau of Standards. This act as the single representation of the South African Industry and Defense input into ISO 8000. In 2014 Dr Salomon was appointed as an Affiliate Faculty member of University Arkansas Little Rock (UALR) to assist the UALR IQ program through expert advice, teaching and student supervision. This was followed by the establishment of the Pilog Global Academy that will serve as a hub whereby industry- derived best practice and academic developments will be used for tertiary master data courses supplemented by Pilog Master Data Solutions being made available to global participating universities and academic institutions.

In just 15 minutes, see how some of the world’s most secure and data-intensive organizations have leveraged Coginiti to dramatically boost data team productivity and accelerate time-to-insight. Through real-world use cases, we’ll highlight how Coginiti empowers enterprises to improve collaboration, adopt modern technologies like open table formats, and lay the groundwork for AI-driven transformation – helping them save millions of dollars while we’re at it. Walk away with practical strategies to make your data operations more agile, efficient, and organized to deliver value.

Chris Coad is the Senior Vice President of Customer Development at Coginiti, a leading provider of collaborative data analytics solutions. In this role, he oversees sales, marketing, and account management, driving the company’s mission to empower organizations with consistent and efficient data-driven decision-making. Before joining Coginiti, Chris held various leadership positions across the tech and analytics sectors. He co-founded and served as CEO of Vinsnap, a connected car platform designed to assist automotive dealerships track their service loaner vehicles. His career also includes roles at Ford Motor Company, Accenture, Compete, Inc., and Leapfrog Online, where he focused on client services and account management. Chris holds a Bachelor of Science in Management from Purdue University and is based in Atlanta, Georgia. Beyond his professional endeavors, he is an entrepreneur, sports enthusiast, and outdoor adventurer.

This session will discuss data licensing/sales from a practical perspective, noting some best practices and potential pitfalls companies should consider in relation to data monetization. Specifically, themes covered will relate to compliance concerns, evaluation of product-market fit, and revenue maximizing strategies. Neudata’s consulting practice focuses on helping companies build and execute monetization strategies and each theme will be explored through past real-world experience.

Henry is a consultant with Neudata, the worlds foremost authority on external data products. Specifically, he focuses on helping companies navigate their data strategies, whether that involves creating valuable data products that align with their business goals or locating external data sources that can be additive to their strategies. Over the last 2 years at Neudata, Henry has helped support over 35 corporations realize their data monetization or purchasing goals.

Where does your budget go? In this rapid-fire session, Milind outlines how CDOs unknowingly spend most of their dollars keeping bad infrastructure afloat. With anonymized use cases, he exposes the invisible costs in Spark workload and shares a blueprint for freeing budget to fund AI and governance priorities.

Milind has over 23 years of experience transforming enterprise data strategies, shaped by an early encounter with a costly data failure at a Fortune 500 company. He helped build some of the era’s largest data warehouses at Microsoft and IBM, witnessing the gap between data investment and business value. To address rising data computing costs, Milind launched Yeedu—a re-architected Spark engine that cuts data processing expenses by 60% and boosts performance by 4- 10X without requiring migration or refactoring. Holding six patents, he now focuses on scaling Yeedu and mentoring the next wave of data innovators.

Join us for a speed round of industry use cases and client stories demonstrating how data products shorten time to insight, increase productivity and expand margins, finally delivering on the promise of business value.

Danielle is an enterprise technology executive and data integration strategist driving high-performance agile teams to deliver business value. Her career emphasis over the last 20 years is application development, holistic data management, next-generation analytics, artificial intelligence/machine learning innovation, and cloud modernization. She is presently a managing director in the KPMG Lighthouse practice, focused on the KPMG Modern Data Platform and sales engineering for go-to-market—positioning data and analytics services with clients and expanding data-related alliances. Prior to KPMG, Danielle served as the regional data officer for Nissan Americas, leading Data and Analytics, Enterprise Architecture, DevOps, and Cloud Delivery. Danielle’s experience as a software engineer has been a driver for success throughout her progression into technical leadership and creating a data-driven culture. Her passion for advancing data accessibility and collaboration at scale is based on unifying business and technology teams to work on strategic data initiatives. Danielle is an advocate for data literacy, persona-based technology enablement, and adoption of privacy engineering at scale.

AI isn’t magic, it’s math fueled by data. Most organizations face significant barriers turning raw, siloed, and messy data into authoritative, usable assets that drive value. We’ll share how Informatica helps enterprises unlock their data potential through a modern approach to data readiness. We’ll showcase examples of how the Informatica platform improves data quality, discoverability, and governance, enabling better analytics, smarter AI, and faster time to insight. Whether you’re starting your AI journey or looking to scale confidently, we will highlight how a strong data foundation is not just a technical imperative, it’s a business differentiator.

Eugene Ma serves as the Global Community of Practice Leader for iPaaS, specializing in Business Process Automation, Cloud Modernization, and Connected Data Management. Over his 25-year tenure at Informatica, Eugene has spearheaded enterprise data warehouse implementations for major clients, led integration specialist teams, and established the strategy, execution, and technology team, influencing Informatica’s solutions and product development. Currently, he is dedicated to delivering Informatica’s iPaaS strategy to customers and driving new use cases.

In just 15 minutes, discover how your data strategy stacks up against the competition. We’ll spotlight the common roadblocks holding teams back—and more importantly, how to blast through them. You’re likely sitting on a gold mine of untapped data potential. Let’s talk about how to turn that hidden value into real business impact. This isn’t a sales pitch—it’s a fast, focused conversation that could unlock serious ROI. You’ll walk away with insights your peers are already acting on. Why wait to find out what’s possible? Let’s turn your data into dollars, for you and your customers—starting now.

Dennis Brown is the Vice President of the Data Practice within New Era Technology, a global technology solutions provider that helps organizations securely connect people, places, and information. In this role, he oversees the delivery of data services that cover strategic data management, data integration & architecture, BI & analytics, and AI & Machine learning. Prior experience includes decades of technical and organizational leadership in the analytics sector. He has a crisp focus on delivering real measurable business value by leveraging both internal and external data sources, developing and leading exceptional delivery teams, and optimizing development and delivery processes. He holds both an MBA and a Masters of Science in MIS from the University of Pittsburg and is currently based in Indianapolis, Indiana. Outside of his professional pursuits, he enjoys outdoor adventures with his family.

The rapid rise of Generative AI presents an unprecedented opportunity—and challenge. While GenAI is adept at producing insights and automating tasks, its effectiveness hinges on access to high-quality, contextual, and interconnected data. This is where knowledge graphs and graph analytics come into play, offering CDOs a powerful framework to organize, enrich, and operationalize data for maximum AI impact. This session will use real-world case studies to illustrate how integrating knowledge graphs with Generative AI can: – Break down data silos to create a unified, enriched source of truth. – Enhance AI’s contextual understanding, resulting in more accurate and actionable outputs. – Enable faster decision-making with real-time graph analytics on complex relationships. – Future-proof your data strategy by building AI-ready data architectures.

Dr. Victor Lee is the Head of Product Marketing at TigerGraph. He has held numerous leadership and specialist roles at TigerGraph since joining in 2014. He combines technical knowledge in graph analytics, databases, and ML/AI with strengths in strategic planning, communication, customer/user experience, and leadership to help to bring to market category-leading graph analytics & AI products. He is the author of Graph-Powered Analytics and Machine Learning with TigerGraph. At TigerGraph, he has previously served as Head of Product Strategy/Developer Relations and Head of Machine Learning/AI. He has degrees from UC Berkeley (BS Electrical Engineering and Computer Science), Stanford University, (MS EE) and Kent State University (PhD Computer Science, research on graph data mining). Before TigerGraph he was a visiting professor at John Carroll University.

This presentation will explore Computational Governance (CG) as an indispensable paradigm automating oversight in today’s complex digital landscape. We will define CG as the use of software code to streamline governance processes, contrasting it with traditional, e-governance, and algorithmic governance models. A key focus will be Federated Computational Governance (FCG), an emerging research area vital for distributed data architectures like data meshes, which balances centralized standards with decentralized autonomy to foster agility and innovation. The presentation will highlight the technological pillars enabling CG, including the synergistic roles of AI for proactive risk identification and automation, blockchain for immutable data provenance and trust, IoT for real-time operational control, cloud computing for scalability, and data analytics for continuous policy refinement. We will delve into real-world applications and supporting products, showcasing examples from both public (e.g., fraud detection, smart cities) and corporate sectors (e.g., A sports major, A Financial Services Major). Finally, we will address critical challenges such as algorithmic bias, privacy concerns, and accountability gaps, offering recommendations for responsible and ethical implementation to harness CG’s transformative potential for more effective, equitable, and trustworthy digital systems.

Technology executive with over 20 years of experience in data, AI, and analytics across a wide range of industries. Specialized in data modernization strategy, analytics strategy, and translating digital imperatives into intelligent, outcome-driven solutions. Proficient in strategic thought leadership, execution planning, solution architecture, product design, and identifying monetization opportunities. Skilled in defining success metrics, driving adoption through change management, and fostering a culture of innovation. Experienced in building high-performing teams and enabling collaboration across cross-functional groups to accelerate impact and deliver measurable results.

Regulators from around the world are rethinking their approaches and adopting agile, iterative, and collaborative models to drive regulatory reform. There is an unprecedented need to analyze the vast corpus of regulatory stock, to modernize and transform regulation. Deloitte’s RegExplorer™ combines subject matter expertise with Augmented Intelligence to deliver practical solutions. Our cutting-edge artificial intelligence digests, analyzes, and understands links within a regulatory corpus and across institutions, allowing you to discover opportunities to accelerate and streamline regulatory reform and burden reduction efforts.

Matt Gracie is a Managing Director in the Strategy & Analytics team at Deloitte. He leads Deloitte’s GPS NLP/Text Analytics practice (ContextEdge, Regulatory Explorer) that supports Civilian, Defense, National Security and Health sector agencies gain insight from unstructured data, such as regulations, to better serve their mission. Over the years Matt has pioneered the engagement of new technologies that are now commonplace in our society – from ecommerce to artificial intelligence. With over 30 years-experience in financial services and consulting, Matt is a thought leader with global and national experience in strategy, analytics, marketing, and consulting.

Data chaos—duplicate records, missing values, and inconsistent formats—can derail analytics, erode trust, and stall innovation. Join us for a hands-on demo of DQLabs, the AI-driven Data Observability and Quality platform that helps you move from reactive firefighting to proactive, automated data confidence.

A seasoned Techno-Functional executive with over 25 years of experience across Fortune 200 companies in Banking, Hospitality, and Retail. Known for building and scaling startups from ground zero to maturity, with a strong focus on product architecture, customer success, and global delivery models. Demonstrated ability to bridge business and technology, drive innovation, and lead high-impact teams through periods of rapid growth and transformation

In the age of AI-native architectures, semantic business ontologies are the key to unlocking governed autonomy at scale. This session explores how ontologies empower AI agents with structured business knowledge, enabling A2A (Agent-to-Agent) collaboration across complex data ecosystems. Coupled with a robust Model Context Protocol (MCP), these agents can reason, govern, and act with precision—delivering business-aligned decisions at machine speed. Learn how ontology becomes the backbone of both autonomous behavior and controlled governance in next-gen enterprise systems.

Inna Tokarev Sela is the founder and CEO of illumex.ai, a company revolutionizing data potential with its Generative Semantic Fabric. Recognizing the complexities of unifying business data semantics—essential for GenAI readiness—illumexc created a platform that simplifies semantic mapping and alignment. illumex is widely used by data-intensive enterprises for GenAI, Data Governance, and multi-cloud initiatives, ensuring swift and error-free data-driven decisions. Inna’s career reveals a consistent theme: bridging the gap between data investments and decision-making. She previously held roles as VP of AI at Sisense and Senior Director of Machine Learning at SAP. An inventor with multiple patents, she speaks frequently at top data and AI conferences. Inna holds an MSc in Information Systems focused on neural networks and completed the Stanford MBA executive program. She also leads the Women in Data Israel chapter.

As data becomes a core business asset, organizations struggle to balance control with agility. In this session, Incept Data Solutions will share how business and technology leaders can quickly establish a strong data governance foundation—without disrupting operations or overcomplicating toolsets. We’ll highlight how enterprises across industries have partnered with Incept to unlock value from their data by simplifying governance processes, aligning with business outcomes, and enabling faster decision-making. Whether you’re starting your data governance journey or modernizing existing capabilities, learn how our proven frameworks help reduce cost, accelerate ROI, and drive executive alignment within 90 days.

Benaka Harish is a Sr. Data Governance Consultant at Incept Data Solutions Inc., where he helps organizations rapidly transform fragmented data environments into streamlined, scalable governance ecosystems. With over 13 years of experience and certifications in Informatica and CDMP, Benaka brings deep expertise in aligning strategy with execution across industries like healthcare, government, and education. Currently pursuing a Ph.D. in Information Quality at the University of Arkansas, Benaka is passionate about turning complexity into clarity. His pragmatic approach to data governance—grounded in frameworks like DAMA-DMBOK and DCAM—has enabled teams to move from chaos to clarity in just months.

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Master Data Management is not a new discipline, yet so many people come away from their MDM deployment feeling underwhelmed or distracted by unnecessary overhead rather than empowered to improve business results. Tamr is changing the game. Join us for this session where we’ll show how companies choosing Tamr’s AI-native MDM are happier with a solution that allows data professionals to: • Configure master data workflows without getting bogged down by rule definition and maintenance (faster) • Manage a single workflow supporting data mastering, data quality, and data enrichment (cheaper) • Power enterprise applications with clearer views of mastered entities and the relationships between them (better)

Ravi Hulasi is the Head of Strategic Solutions at Tamr, where he leads efforts to help organizations unlock the full value of their data through strategic guidance and implementation expertise. He works closely with clients to drive successful adoption and measurable impact from Tamr’s data mastering solutions. With over 20 years of experience in enterprise data management and technical leadership, Ravi has a proven track record of developing innovative solutions and bringing cutting-edge products to market on a global scale.

It’s fascinating to consider that the value in our data hasn’t diminished; rather, our ability to access and utilize it has evolved, especially with the advent of enterprise AI. We’re now at a point where we can effectively unlock the value hidden within unstructured data – formats that were previously too intricate and expensive to decipher. Many organizations find that this substantial volume of unstructured data remains largely inaccessible and, as a result, underutilized. In essence, this unstructured data represents a considerable and mostly untapped resource. Leveraging AI offers the most effective approach to reclaiming unstructured data. Discover how Intelligent Data Classification (IDC) can analyze text, image, and video files to automatically identify and label sensitive, confidential, or personally identifiable information (PII). Learn how rich metadata can be generated, facilitating robust data governance policies. The capability of AI to automate the classification of extensive amounts of dark, unstructured data represents a significant breakthrough that was simply unattainable before.

John Ottman is Executive Chairman of Solix Technologies, Inc. and brings over 25 years of industry experience. Mr. Ottman is also Chairman and Co-Founder of Minds.com a leader in open source social media. Previously, Mr. Ottman was President and CEO of Application Security, Inc., President of Princeton Softech, Inc., and Executive Vice President, Worldwide Markets at Corio, Inc.. He also has held key senior management roles at Oracle and IBM. Mr. Ottman began his career in sales at Wang Laboratories, Inc. where he became a Branch Manager. He then joined Oracle for 10 years serving in various field executive positions including Group Vice President, Industrial Sector. In 1999 Mr. Ottman joined cloud industry pioneer Corio, Inc. as Executive Vice President, Worldwide Markets. At Corio he led the company from the startup phase to an early cloud industry leadership position resulting in an IPO and acquisition by IBM in 2004. He then joined IBM to manage the integration of Corio into IBM Applications on Demand. Later he joined Princeton Softech, Inc., as President, Global Operations. Princeton Softech, Inc., a high growth company and leading provider of enterprise data management software, was also acquired by IBM in 2007. Mr. Ottman then rejoined IBM to run worldwide sales for the IBM Optim product line. In 2008 Mr. Ottman joined Application Security, Inc. and served as President and CEO until 2012. Application Security, Inc., a leader in database security, risk and compliance was subsequently acquired by Trustwave Holdings, Inc. Mr. Ottman is also author of the database security book, Save the Database, Save the World!. He holds a B.A. from Denison University.

As the AI-native data stack takes shape, If your data isn’t reliable at the source, your AI is learning the wrong thing. In this session, Telmai co-founder and CEO Mona Rakibe shares why data observability must be baked into the lake, not bolted on. She’ll show how leading teams are embedding observability directly into modern lakehouse architectures by using Telmai to monitor raw, messy, and semi-structured data from the moment it lands, across open formats like Apache Iceberg and Delta Lake. You’ll walk away with real-world patterns and strategies to ensure your data is trustworthy before it powers agentic workflows, LLMs, or BI dashboards. If you’re serious about operationalizing AI, this is where the work begins

Mona Rakibe is the Co-founder and CEO of Telmai, a modern data observability platform helping enterprises build AI-ready data pipelines with trust at the core. With over two decades of experience in data infrastructure and enterprise software, Mona has led product and engineering teams at industry pioneers like Informatica and Reltio.

Data leaders know that trust in data is non-negotiable. In this fast-paced 15-minute session, Nandagopal Jayaram will demo QGrid – a powerful new data reliability platform built for the AI era. See how QGrid combines automated data observability with AI-driven quality monitoring to proactively detect issues, pinpoint root causes, and raise incidents before they disrupt operations. If you’re responsible for scaling trusted data across your enterprise, this is the tool – and the demo – you don’t want to miss.

Nan Jayaram is the founder and CEO of CoStrategix, a strategy-led digital and data transformation services firm that helps organizations transform to stay competitive in today’s digital world. Nan’s strength is applying technology to achieve new revenue streams or operational efficiencies. He loves to stay on the leading edge of all things related to digital transformation, data and analytics, artificial intelligence, and the cloud. Nan defines his mission as tapping into the collective curiosity of employees and partners to create new possibilities for clients, communities, and each other.

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AI initiatives are only as strong as the data that fuels them. In this session, we’ll demystify the concept of Data Readiness—what it means, why it matters, and how it directly impacts the success of AI-driven strategies. You’ll get a look at our Data Readiness Hub, a centralized solution designed to deliver clean, curated, contextual, and continuous customer data—ready to deliver on AI success. Don’t let bad data hold you back—join us to turn it into your competitive advantage.

Steve Zisk is a seasoned technology professional with more than 35 years of expertise in software engineering and product marketing. As Product Marketing Principal at Redpoint Global, Steve is tasked with developing messaging and marketplace positioning for Redpoint’s customer engagement platforms.

Join us for a light-hearted talk about a really serious topic. How to avoid the GenAI distractions which can get in the way of unleashing incredible LLM capabilities on solving the business problems which truly drive your success. Think about the kinds of problems you deploy experienced executives, teams of data scientists or expensive management consultants to solve. The kinds of problems which your Board wants to know if you have solved. The type of operational changes which can give you an edge over your competitors. P.S. Your bit “Don’t ask GenAI to water your office plants—ask it to fix your supply chain or your customer churn rate.” made me think of Kennedy’s “ask not what your country can do for you…” may be Ask Not What LLMs Can Do For You—Ask How They’ll Supercharge Your Business KPIs

Avrom is a highly experienced hi-tech executive with more than 20 years of experience managing, funding and driving growth at rapidly growing technology companies. Avrom’s former roles include COO of both SimilarWeb (NASD: SMWB) & Seeking Alpha as well as being a Board member of a number of high-growth companies. In addition, Avrom has spent a number of years in investment roles at Jerusalem Global Ventures and ION Asset Management.

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Data governance has never been more important for organizations. Data is proliferating across an increasing number of sources, applications and clouds, much of it in multiple formats. Generative AI (gen AI) and large lang uage models (LLMs) are incorporating massive data sets that include sensitive data such as personal identifiable information (PII) and confidential medical and financial details. Companies must be able to unify, classify, analyze and share this data to gai n actionable insights while protecting it from unauthorized access and staying in compliance with regulations. It’s critical to have a strong governance foundation not only for data, but also for applications and AI assets, in one platform. This session will touch upon a framework that unifies data and AI governance.

Ms. Dember is currently the Data Governance Lead for Datavail, specializing in modern day frameworks that are more agile, easier to implement and are enhanced to support AI. She is credited as one of the founding principles of Data Governance, having published the first Data Governance Maturity Model at DAMA Conference in 2004. Since then, she has published works on Data Analysis and has both lectured and taught courses on data governance at conferences both domestically and abroad. She has been responsible for transforming business analytics into solutions that provide actionable information to drive business growth, Customer and Consumer insights, as well as developing strategic working relationship between IT and the business units supported within the organization. Ms. Dember is considered an industry thought leader in all aspects of data management and currently is providing advisory consulting services to organizations that are looking for assistance in growing their capabilities, need direction on resolving issues or figuring out priorities, or providing insight to current/future trends in data governance. Ms. Dember is one of the 4 subject matter experts leading the CDO Certification Program administered by the CDOIQ Program led by Dr. Wang. She is also a mentor for the Woman in Data Program administered via the EDM Council.

Recent headlines, from Reddit licensing its data to Google to Instacart building a robust advertising business, have put data monetization squarely on the executive agenda. Despite this growing interest, many companies grapple with inflated expectations and lack a systematic strategy to generate scalable value from their proprietary data. Our research, encompassing over 30 case studies and interviews with a dozen data executives, uncovers three common misconceptions and outlines key principles for success. This presentation will showcase real-world examples of organizations achieving significant data monetization and provide actionable best practices to help you get started.

Mohammed Aaser is Domo’s Chief Data Officer (CDO), where he helps customers create innovative data products that deliver business impact. He also works closely with company’s data and technology partners to extend the power of Domo’s robust ecosystem of integrations. Prior to Domo, Mohammed was CDO at McKinsey and Company, where he championed the strategic use of data across thousands of client initiatives. He led the firm’s data innovation capabilities, accelerating development of data products by combining deep industry knowledge with cutting-edge data sets, data management technology and data engineering. He also helped launch and build McKinsey’s analytics practice – focused on helping companies scale their data and AI initiatives – and served as the practice’s head of operations and strategy. Prior to McKinsey, Mohammed held leadership roles at Ameriprise Financial, where he led the organization’s marketing strategy and analytics transformation. Mohammed received his bachelor’s degree from the University of Minnesota and an MBA from Harvard University.

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While your competitors drown in unstructured data overload, elite enterprises are weaponizing their messiest information—PDFs, emails, call transcripts—into profit machines using Flexor’s data transformation platform. Discover how companies process 10x more complex data and crush AI project timelines from 6 months to 3 weeks. Learn the game-changing frameworks that turn your data disasters into competitive dominance—without breaking your existing systems. This isn’t a theory. This is your unfair advantage.

As CEO of Flexor, Or Zabludowski is a visionary leader in unstructured data solutions. With an MSc in Biomedical Engineering, he led Israel’s National Covid HQ Data Team, delivering mission-critical insights that shaped national decisions and earned top tech honors. Now at Flexor, he is pioneering next-generation data infrastructure, transforming how enterprises extract, structure, and operationalize unstructured data to drive intelligence and innovation at scale.