This panel discussion will explore how professional associations and certifications can enhance the careers of analytics professionals. This session will shed light on how association memberships and certifications open doors to networking opportunities, continuous learning, career advancement, and industry recognition. Attendees will gain new insights about how active participation in professional communities and earning certifications can influence their career trajectory, marketability, and professional growth in the ever-evolving domain of analytics. This discussion is a must-attend for anyone looking to elevate their analytics career.

This isn't your typical tech talk—it's a story of the journey into how big players like LinkedIn, Uber Eats, and Stripe are mastering the art of real-time data. Viktor is here to demystify Apache Pinot's superpowers, showing you how it instantly transforms mountains of data into actionable insights. Business decision-makers have long had access to dashboards and reports, but now analytics can be made available to users as features of stickier, more engaging applications. With stories, insights, and a touch of humor, Viktor will unpack the cool features of Apache Pinot, including the Star-Tree Index, and show you why it’s a game-changer in data strategy. This session is for everyone, whether you're a data geek, a business guru, or just curious about the future of tech. Viktor's dynamic style will keep you on the edge of your seat, eager to implement these insights. So, buckle up and get ready to be wowed by the power of real-time analytics with Apache Pinot – it will be a blast!

Have you ever wondered how a data company does data? In this session, Isaac Obezo, Staff Data Engineer at Starburst, will take you for a peek behind the curtain into Starburst’s own data architecture built to support batch processing of telemetry data within Galaxy data pipelines. Isaac will walk you through our architecture utilizing tools like git, dbt, and Starburst Galaxy to create a CI/CD process allowing our data engineering team to iterate quickly to deploy new models, develop and land data, and create and improve existing models in the data lake. Isaac will also discuss Starburst’s mentality toward data quality, the use of data products, and the process toward delivering quality analytics.

Customer Lifetime Value (CLV) is the cornerstone of any recurring-revenue or service business. It's one of the most important metric in contemporary business analytics, showing the long-term profitability and sustainability of customer relationships.

In this session, Ranjeeta Bha will explore the significance of CLV, how it's calculated, and the many factors that influence it such as customer acquisition costs, retention strategies, and revenue forecasting. We'll explore what makes customers quit—and how to predict it. Attendees will understand how to gain a comprehensive understanding of their customer base, as well as how emerging statistical and AI approaches can be used to estimate CLV.

Join the team from Moody's Analytics as they take you on a personal journey of optimizing their data pipelines for data quality and governance. Like many data practitioners, Ryan understands the frustration and anxiety that comes with accidentally introducing bad code into production pipelines—he's spent countless hours putting out fires caused by these unexpected changes. In this session, Ryan will recount his experiences with a previous data stack that lacked standardized testing methods and visibility into the impact of code changes on production data. He'll also share how their new data stack is safeguarded by Datafold's data diffing and continuous integration (CI) capabilities, which enables his team to work with greater confidence, peace of mind, and speed.

Join our panel of experts in exploring the cutting-edge realm of Decision Intelligence and discover how it diverges from traditional Data Analytics and Business Intelligence, reshaping the landscape of strategic decision-making. Our panel explores real-world instances where Decision Intelligence catalyzed profound organizational shifts, yielding tangible results. This is a not to miss session examining the future of decision-making and how to harness balance between forecasting and human oversight for maximum efficiency! 

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. 

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.

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.

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.

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.

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.

In this executive debate, leading industry analyst Mike Ferguson welcomes leaders from premier software companies to discuss key topics in data management and analytics. Panelists will debate the impact of Generative AI, the implications of key industry trends, how best to deal with real-world customer challenges, how to build a modern data and analytics (D&A) architecture, data and AI governance and sharing, and on-the-horizon issues that companies should be planning for today.

Attendees will learn best practices for data and analytics implementation in a modern data-driven enterprise from seasoned executives and experienced analysts in a packed, unscripted, candid discussion.

Being a solitary data scientist can be lonely, whether in an embedded role or pioneering data science adoption within an organization. As you collaborate with individuals with varying business contexts, subject-matter expertise, and data backgrounds, there are strategies you can apply to set yourself up for success.

 In this session, Lauren Burke will demonstrate how solitary or siloed data scientists can thrive by gaining support and buy-in from key stakeholders. She'll cover the "road trip" strategy for identifying allies and finding quick wins to demonstrate value. She'll also discuss communicating the difference between traditional analytics and data science, as well as techniques for educating stakeholders and leveling up junior practitioners.

 Attendees will learn how to identify organizational needs and effectively scope projects, ensuring alignment with business objectives and defining clear measures of success while identifying opportunities to deliver incremental value. We'll cover the importance of creating end-user-focused documentation, where it should live, and how to use "SEO" to make your data science presence more visible. 

Many organizations strive toward data-driven, yet most of them struggle to get relevant insights to the right stakeholders in a timely manner, resulting in a reactive rather than proactive approach. Given a world of fast-paced data intake and customer expectations of real-time, drawing insights and making decisions faster are critical paths to building timely and contextual relevance with customers. Join Murli Buluswar, Head of Analytics - US Personal Bank at Citi, to learn how delivering preemptive solutions though leveraging next generation technologies increases operational efficiency. Murli will discuss how to use conversational Generative AI to increase democratization of intelligence and reduce the friction between data, insight, decision, and outcome.

This presentation covers the critical transition from traditional analytics to the strategic integration of AI into business processes, from the compelling reasons for adoption to the practical implementation steps. The 'What' segment introduces the foundational elements enabling the AI revolution and the business processes ripe for disruption. Addressing the 'Why', we highlight the responsible adoption of AI with accurate, reliable data as the backbone of any AI-driven initiative. This section underscores the need for solid data benchmarks and testing to measure AI's effectiveness, to ensure that AI implementations lead to tangible, positive outcomes, and to alert leaders to issues early. The 'How' section provides actionable insights on implementing AI to scale data-driven decisions effectively. With real-life examples, this section covers best practices for data management, technology integration, and strategies for fostering a culture that embraces data and AI. Attendees will learn about scaling AI-driven analytics, including considerations for data security, privacy, and ethical AI use.

This presentation explores the challenges and evolution in data and technology, emphasizing the growth of data sources, user concurrency, and distributed ownership. It delves into the strategic significance of a unified analytics tier to enable a Phase 2 of virtualization. Key components like an Entitlement Service, Data Catalog(s), MALT, and Data Contracts are discussed and what has been learned forcing those technologies and patterns to also evolve. This presentation underscores the importance of aligning with business outcomes, tracking the influence on Total Cost of Ownership (TCO), and establishing or improving a governance strategy as the organization matures.

Join us as we go from zero to insights in 15 minutes. Alex will build an entire analytical report, from SQL query to python to data visualization. We’ll cover the basics of a modern data notebook, some of the technical AI Magic behind the scenes, and show how hundreds of customers accelerate time to insight with Hex.

In this fireside chat, Mike Ferguson—Europe’s leading industry analyst in data management and analytics—talks to Rob Thomas, Senior Vice President and Chief Commercial Officer at IBM on what IBM is doing to help companies get maximum business value from data and AI.

The discussion will explore what IBM sees as the key things needed to become successful with AI. This includes talking about embracing hybrid cloud computing to support data and deploy AI anywhere; dealing with the challenge of distributed data estate; and exploring integrated data and AI technology stacks and AI assistants that help companies tear down data silos, share data, and quickly build and integrate AI, augmentation, and automation into every part of their business. Finally, it will also explore how IBM is helping accomplish this while maintaining end-to-end data and AI governance.

The Data Engineer's role amidst the rise of big data, cloud computing, and AI-driven analytics has shifted. This panel chat explores the ever-changing landscape of essential skills and the automation of outdated ones. With a myriad of architectural options available, we'll dissect how organizations navigate the complexities to tailor solutions to their specific needs. Let's unravel the intricacies of building scalable data systems, pinpointing common breakpoints and strategies for efficient scaling. Come along as we delve into in constructing the foundation of the data-driven future.

The data mesh framework, first introduced in 2021, provides a more dexterous and valuable approach to data management by increasing accessibility for teams, partners, and other stakeholders. In this session, Annalect’s Chief Technology Officer, Anna Nicanorova, and Director of Data Engineering, Santhosh Swaminathan, will share how their organization — the data and analytics division of Omnicom Group — was able to simplify the implementation of data mesh and unlock numerous benefits — namely, the ability to facilitate seamless collaboration and drive greater operational efficiency. 

Companies need reliable information about the future to make decisions in the present. Strategic plans and budgets rely on good guesses about what the future holds. But typical approaches to planning are often rarefied and insulated from the real world. There's an approach developed in Switzerland and Southern California that holds real promise: Gamification.

Games are inherently competitive—which means the player with the optimal strategy prevails. That optimization can be applied to forecasting and prediction, yielding significantly better results. David Savlowitz offers a peek into gamified forecasting, a convergence of competitive gaming, investment strategy, data science, and human psychology that enables accurate forecasts.

In this session, David will explain how competitive approaches can involve a wider group that includes economists, data scientists, and non-technical staff; and how tournament models where players are rewarded for accurate predictions that maximize return on investment and minimize forecasting error.

As the field of data analytics continues to progress and expand, the role of semantic layers in harnessing the power of AI is becoming increasingly crucial. The incorporation of context and constraint is essential to optimizing the potential of Language Model Models (LLMs), which requires a more structured and specialized approach. While traditional methods have made strides in providing some context through prompt engineering and knowledge graphs, semantic layers offer unparalleled clarity and efficiency in bridging the gap for LLMs. To further unfold the narrative on semantic layers and their transformative impact on AI-enabled analytics, we invite you to a thought-provoking session with Artyom Keydunov, Cube's CEO & Co-founder.

Join Jamie Underwood and Andy Hannah for a transformative deep dive into the Responsible Data Revolution. In this session, they'll explore the crucial intersection of innovation and advanced analytics, delving into the legal aspects surrounding it. With Jamie's expertise in navigating the intricacies of intellectual property and Andy's deep entrepreneurial and analytical experience, we'll uncover the ethical and legal considerations that arise in the era of big data and AI. 

From privacy concerns to intellectual property rights, they'll discuss the evolving landscape of data governance and responsible innovation. Gain insights into strategies for leveraging data ethically and responsibly while maximizing its potential for transformative innovation. This session promises to equip you with the knowledge and tools to navigate the complex terrain of the data revolution responsibly.