Drawing on his 2023 book ‘Confident Data Science’, Adam Nelson will show you how to measure your organization's data culture. Learn how to use this key metric to understand how well your organization’s culture performs along four key dimensions: Offering access to quality information about the data it has; providing the right access to the right people at the right time; investing in data skills development; and maintaining high data quality standards.

The emergence of pre-trained deep learning models – e.g., Foundation and generative AI models – such as GPT-4, represents a paradigm shift in the utilization of AI. This keynote, rooted in the insights from "AI iQ™ for a Human-Focused Future," explores the profound differences between implementing these state-of-the-art pre-trained models and traditional machine learning/AI approaches. Find out why the ‘xOps’ paradigm is a fallacy, why the unique technical and operational challenges necessitate sophisticated data and model observability and the imperative for advanced and specialized computational infrastructure to support the intensive demands of these models.

We delve into the strategic considerations surrounding data governance, ethical AI use, and the integration of AI into business processes, underscoring the need for a comprehensive framework that encompasses technological implementation and alignment with organizational goals and values. The discussion extends to the critical role of having a single leader for AI – the Chief AI Officer.

Through a blend of strategic insights and practical examples, this presentation offers a roadmap for businesses looking to navigate the complexities of integrating these models. It provides actionable strategies for building the infrastructure, culture, and processes necessary to harness the transformative potential of these technologies, driving innovation, efficiency, and growth in the digital era. Join us to explore how your organization can transition from traditional AI methodologies to leveraging the power of generative models and observability ensuring a competitive edge in the rapidly evolving corporate landscape. 

The ability to convey insights effectively is paramount in building bridges between analytics teams and the wider enterprise. Data storytelling transforms complex data sets into compelling narratives that resonate and shift with our audiences. We will discuss the importance of identifying your audience's needs, selecting relevant data points, crafting engaging story structures, and employing visualizations. We will uncover the importance of the 'enterprise pulse' - or the triggers and feedback loop that reinforce regular communication with stakeholders. Effective and consistent data storytelling is the key to clearer communication, informed and improved decision-making, and establishing meaningful connections with stakeholders. Most importantly, we will share practical examples to arm attendees with a strategy that results in data & analytics champions throughout the enterprise. 

Following the explosion of ChatGPT onto the market in late 2022, LexisNexis Legal & Professional quickly saw the massive opportunity for large language models (LLMs) to transform how its customers do legal work. Within weeks, the company pivoted to begin innovating, delivering, and now expanding generative AI solutions for its customers. Across legal and tech industries, the company was recognized as a generative AI leader.

LexisNexis EVP & CTO Jeff Reihl will detail how the company rapidly innovated, delivered, and expanded generative AI solutions. Reihl will share insights into how the company considers its customers’ key challenges and its multi-model approach, prioritizing the best LLM to solve each customer use case. He’ll also share how the company integrates its data assets with LLM technology to improve model output and how the company’s Retrieval Augmented Generation (RAG) platform creates flexibility for the company to adopt new LLM technologies as they change. 

Attendees will learn strategies for deploying generative AI in their organizations to impact products, customers, and internal tools. Reihl will share how attendees should think about deploying generative AI in their organization, how to hire for it, and how to organize teams around it.

Data processing across systems relies on data lineage, a crucial aspect that tracks the movement and transformation of data records. Data lineage is necessary for Data Operations and Governance that support incident response, legal investigations, and privacy and compliance standards. However, things can go wrong due to the proprietary hand-coded business logic that alters the data. When that happens, the current data lineage systems that operate at the dataset/table level are not very helpful. They require additional analysis effort that can be expensive and time-consuming. In today's data landscape, we need a record-level lineage that can pinpoint the exact source and cause of data issues with minimal manual intervention. This problem has long been neglected due to its complexity, but we have a solution to propose. In this presentation, we will introduce a novel concept and its reference implementation using Starburst Enterprise Platform.

They see your every move! You know it’s true: Your data is everywhere, the fingerprints of your behavior and movements captured by all manner of apps and devices. Does privacy still exist? The short answer is no, but striving toward it will help mitigate the many risks of inappropriate data access, and that’s really what “privacy” is all about these days! Check out this Fireside Chat with Data Warrior Kent Graziano and DM Radio Host Eric Kavanagh to learn more! They’ll talk about practical methods for designing and managing data governance programs, security protocols and most importantly: responsible behavior!

In today's data-driven landscape, optimizing AI data processes isn’t a nice-to-have—it’s a strategic imperative. Despite mounting pressure for enterprises to leverage and derive business value from AI, data scientists and engineers are bogged down in data preparation and deployment, reducing their ability to scale AI model development. In this session, discover valuable insights and practical hands-on use cases that show how enterprises can overcome their data-related challenges and help their data scientists and engineers harness the full potential of AI.

As organizations are exploring and expanding on their AI capabilities, Chief Data Officers are now responsible for governing the data for responsible and trustworthy AI. This session will cover 5 key principles to ensure successful adoption and scaling of AI initiatives that align with their company’s business strategy. From data quality to advocating for ethical AI practices, the Chief Data Officer’s mandate has expanded to compliance of new AI regulations. 

Peggy Tsai, Chief Data Officer at BigID and adjunct faculty member at Carnegie Mellon University for the Chief Data Officer executive program, will provide insights into the AI governance strategies and outcomes crucial for cultivating an AI-first organization. Drawing on her extensive experience in data governance and AI, this session will be an invaluable guidance for all participants aiming to adopt industry-leading practices.

We're in the a Cambrian Explosion of data architectures. In the last two years, dozens of vendors have each championed their own version of ‘the modern data architecture solution’, all claiming to be the future of IT in a data-driven enterprise. The sheer volume of architectures is daunting: Streaming data platforms, data lakes, structured/semi-structured/unstructured data, cloud data warehouses supporting external tables and federated query processing, lakehouses, data fabric, and layers of federated query platforms that offer virtual views of data. All claim to support the building of data products.

No surprise that customers are confused as to which option to choose. 

However, key changes have emerged including much broader support for open table formats such as Apache Iceberg, Apache Hudi and Delta Lake in many other vendor data platforms. In addition, we have seen significant new milestones in extending the ISO SQL Standard to support new kinds of analytics in general purpose SQL. Also, AI has also advanced to work across any type of data. 

What does this all mean for data management? What is the impact of this on analytical data platforms and what does it mean for customers? What opportunities does this evolution open up for tools vendors whose data foundation is reliant on other vendor database management systems and data platforms? This session looks at this evolution, helping vendors and IT professionals alike realise the potential of what’s now possible and how they can exploit it for competitive advantage.

Join Anthony Bussanich, Executive Director, Data & Intelligent Automation at JPMorgan Chase as he joins Fiona Sweeney, Partnerships Director at Women in Data® in this essential fireside chat. They will discuss his career to date and explore the importance of a robust data strategy to support businesses as they harness intelligent automation technologies in order to drive improvements in operational efficiency. Anthony will also give us his views of what needs to happen from a people perspective to ensure that organizations optimize resources to harness the opportunity that intelligent automation can bring.

Effective governance is paramount for data leaders to efficiently harness the power of data products among their entire organization. This session delves into the need to foster collaboration between data producers and consumers to ensure seamless interaction and utilization of data assets.

Advanced Analytics, AI, ML, Blockchains, and Platforms are improving human well-being. It is valuable when Advanced Analytics predicts market fluctuations or optimizes customer portfolios. It is convenient when AI and ML improve operational efficiency or recommend the next customer purchase. It is comforting when Blockchains transparently record and preserve incorruptible information. It is commendable when Platforms create multiplier effects for good. It is priceless when these tools work to rescue a life. Could businesses somehow eradicate modern day slavery in their global supply chains with these tools? This task is daunting with thousands of suppliers behind popular products, but businesses are using analytics to find patterns, increase supply chain transparency, reduce reputational risk, and prevent lost revenue, in addition to rescuing lives. In this session, Kendra Taylor of KEYfficiencies, reviews how some businesses use analytics to end human trafficking in global supply chains and what the future might hold.

We are overwhelmed by data today, and as data practitioners and leaders, our job is to aid the business in understanding what messages lie hidden within our data. The best way to make sense of this information overload is through proper data visualization - large amounts of data are easily digestible when represented visually in a graph or picture rather than in a table of numbers. In this session, you'll learn how to tap into the fact that humans are visual creatures. Capturing an audience's attention and displaying information in an interpretable way requires consideration at both the emotional and rational level. Data visualization is not just about technical prowess or business acumen, but also relies on design techniques and psychology. Join and learn how to elevate your data visualizations to the next level or take learnings back for your team - with the ultimate goal of influencing your key audiences through the power of data viz!

Our panel of experts are well versed in the dynamic realm of data stack evolution. We sit them down for a deep dive on the dichotomy between open-source and proprietary platforms, unraveling the "Occam's Razor" for making the best choice. Discover the strategies they've used for agile experimentation with diverse data architectures, adeptly maneuvering through privacy and scalability constraints. This is a must see panel that will give you the tools and tips needed to navigate the ever changing Data Stack.

We're moving into uncharted territories of emerging technologies, poised to revolutionize data science. In this panel discussion, we'll unravel the mysteries of the technological fringes and explore their imminent impact on mainstream adoption.

Our panel of experts will discuss a future where these technologies are ubiquitous, and how to prepare for the transformative shifts in daily life and industry. Let's peer beyond the horizon, contemplating the dawn of a new era in data science and beyond.

This panel delves into the intricacies of building a cohesive and effective data ecosystem that drives organizational growth and innovation. In this session, our panel of experts will explore the foundational strategies for integrating diverse data sources, tools, and technologies to create a unified system that not only supports but enhances decision-making processes. Attendees will gain insights into best practices for data management, the importance of data governance, and how to leverage data for maximum impact. Discover how to navigate the challenges of data integration and use it to foster a culture of data-driven excellence within your organization.

Join us for an enlightening discussion on transforming your data ecosystem into a powerful engine for strategic advantage.

How do you craft a robust AI-focused data governance strategy that addresses not just technical issues, but also legal, ethical, and organizational angles? Any workable strategy must be able to adapt to an AI landscape that's changing almost any day, and will enforce responsible use of data.

In this session, Kristy Wedel will discuss the unique governance needs of AI, the critical importance of high-quality data, and policies that can evolve alongside learning algorithms through continuous assessment approaches. She will inclde data privacy and compliance—with a focus on GDPR and HIPAA—as well as ethical considerations, anonymization, and privacy. Attendees will leave with a practical understanding of documentation and how to equip stakeholders for success. Kristy will also offer practical guidelines for bias mitigation, fairness, and transparency in AI solutions.

This panel of DataVengers looks at the hot topics and emerging technology trends in data, analytics, and AI. Bringing together an enthusiastic team with a diverse background, they'll share tips on putting passion into your job and building your personal brand. Come with questions—not just about where data is headed, but also about standing out from a digital crowd.

The industry has witnessed some tectonic changes over the last few years: on prem to cloud to multi-cloud, BI to AI to GenAI, and data warehouses to data lakes to data lakehouses, to name a few. This constant evolution coupled with the ever-increasing demands of the business makes platform thinking crucial in order to ensure a future-proof infrastructure. As companies race to advance their AI strategies, Dell has seen a gravitational pull towards a modern data architecture that can create high quality data to feed AI and generate high quality outcomes. Join this session to learn about how the Dell Data Lakehouse, powered by Starburst, is the modern paradigm for this new era. You’ll learn about the investments Dell is making in data, analytics, and AI, why Dell and Starburst partnered up on this solution, and how it enables a tremendously powerful yet open and flexible data architecture.

Synthetic identity fraud has been a constant challenge for the financial industry. By creating believable, fake identities, criminals can defraud banks, launder money, and hide ill-gotten gains. 87% of organizations have extended credit to synthetic customers, including 54% who applied for it, and 53% to whom the institution itself offered the credit in the first place. Online banking and digital transactions make it easy to hide automation.

But AI is poised to take this fakery to an entirely new level. Automation lets fraudsters open accounts, make deposits, and perform believable, human-like transactions that make them hard to identify. Combined with generative capabilities that make perfectly deceptive words and imagery, we're on the verge of an identity arms race.

In this session, Deduce's Ari Jacoby will explore how AI is transforming finance, making it harder than ever for financial institutions to discern fake customers from genuine ones. He'll discuss what this post-truth era means for society as a whole, and offer tips and best practices for businesses to counter the impact of AI-equipped bad actors.

Long before Moneyball popularized the idea, stats and data were part of sports. But things have come a long way since then. Join Scott Nestler for an overview of the transformative role of analytics in modern sports. He'll explores how data-driven approaches are revolutionizing performance on the field, enabling athletes and teams to optimize their strategies, enhance physical conditioning, and achieve superior results. Beyond the field, he'll discuss the impact of analytics on the business side of sports, from talent scouting and player valuation to fan engagement and revenue generation.

By integrating real-world examples and cutting-edge research, this presentation highlights the symbiotic relationship between analytics and sports, illustrating how data is not just reshaping strategies but also redefining the very essence of excellence in the sports industry.

For at least a decade, we have established best practices for handling data and making sure it is delivered when needed and is correct. But with the explosion of LLMs and Transformer models, not all of those best practices apply anymore. In this talk, you will learn which best practices still make sense in this new Machine Learning world, and what new strategies you need to adopt to make sure that your LLMs can train properly and return inference in a reliable, timely and *accurate* manner.

In today's complex data & AI ecosystem, organizations prioritize crafting a data strategy designed to democratize access to data, to power their analytics engines. But how much of the data is truly usable? How do you rectify data gaps to ensure AI analytics and insights are grounded in reality without bias?

Referencing a collaboration between Women in Data® and the National Health Service (NHS) in the UK, in this session you will learn how a robust data strategy is critical to effect change and improve patient outcomes in the uniquely sensitive area of Healthcare.

Analytic databases are quietly going through an unprecedented transformation. Open table formats, led by Apache Iceberg, enable multiple query engines to share one central copy of a table. This will fundamentally change the data industry, by freeing data that’s being held hostage by siloed data vendors. In this session to hear from Dan Weeks, co-creator of Apache Iceberg and co-founder & CTO of Tabular, as he will cover the origins and basics of open table formats and show how these new capabilities are shaping the future of both open-source compute projects and commercial data warehouses alike. You will learn key advice for building a data architecture that makes data more accessible to all data practitioners while avoiding vendor lock-in.