Jet2 is redefining the role of data within its business. Jet2's Data Enablement Manager, Stephen Nutter, and Data Science Manager, Kieran Alden are championing a vision that anyone, any platform, anywhere within Jet2 can safely harness the power of data to drive competitive advantage, profitable growth, and operational efficiencies. Learn how Stephen, Kieran and the Data Science team are using Hex to deliver a better data experience through real examples and use cases for the business. 

In this session, Chad Sanderson, CEO of Gable.ai and author of the upcoming O’Reilly book: "Data Contracts," tackles the necessity of modern data management in an age of hyper iteration, experimentation, and AI. He will explore why traditional data management practices fail and how the cloud has fundamentally changed data development. The talk will cover a modern application of data management best practices, including data change detection, data contracts, observability, and CI/CD tests, and outline the roles of data producers and consumers. 

Attendees will leave with a clear understanding of modern data management's components and how to leverage them for better data handling and decision-making.

The quality and usability of data determine the success of data-driven projects, and it has never been more critical to establish an operational pipeline of high-quality data that is both secure and accessible. Once distinct disciplines, Data Governance, Master Data Management, and Generative AI have converged to deliver data that is insight- and AI-ready in record time. Join our experts for practical examples and actionable advice you can use to get started.

Open table formats such as Apache Iceberg, Delta Lake, and Apache Hudi have dramatically transformed the data management landscape by enabling high-speed operations on massive datasets stored in object stores while maintaining ACID guarantees.

In this talk, we will explore the evolution and future of dataset versioning in the context of open table formats. Open table formats introduced the concept of table-level versioning and have become widely adopted standards. Data versioning systems that have emerged more recently, bringing best practices from software engineering into the data ecosystem, enable the management of multiple datasets within a large-scale data repository using Git-like semantics. Data versioning systems operate at the file level and are compatible with any open table format. On top of this, new catalogs that support these table formats and add a layer of access control are becoming the standard way to manage tabular datasets.

Despite these advancements, there remains a significant gap between current data versioning practices and the requirements for effective tabular dataset versioning.

The session will introduce the concept of a versioned catalog as a solution, demonstrating how it provides comprehensive data and metadata versioning for tables.

We’ll cover key requirements of tabular dataset management, including:

• Capturing multi-table changes as single logical operations
• Enabling seamless rollbacks without identifying each affected table
• Implementing table format-aware versioning operations such as diff and merge

Join us to explore the future of dataset versioning in the era of open table formats and evolving data management practices!

Most organizations are using GenAI in hopes of gaining easy access to information needed by their users to enable greater productivity. At the same time, it's also well-documented that LLMs can deliver inaccurate information. To be of value, users need to be able to trust that the answers presented to them are correct.

This is a key issue at the center of AI adoption and its applications in the real world. For example, many organizations are beginning to develop, test, and implement chatbots for internal and external use to provide answers to questions by using natural language. When those chatbots do not produce the right answers, all the time and effort put into creating them ends up wasted.

Join David Jayatillake, Cube's VP of AI, for an in-depth discussion on the current state of GenAI and the rise of the semantic layer.

In this talk, you will learn about:

The current state of GenAI

The rise of the semantic layer in modern data stack with AI

The significant differences between an AI chatbot with and without a semantic layer 

Key business metrics, like Annual Recurring Revenue (ARR), are the lifeblood of every company, but calculating and aligning on these critical metrics can be a daunting task. Inconsistent definitions, siloed data, and lack of collaboration between teams often lead to confusion, inefficiencies, and suboptimal decision-making.

In this session, we'll take you on a journey of how a rapidly growing SaaS unicorn tamed the metric beast by leveraging Sightfull's central store of governed metrics and integrated semantic layer.

You'll discover how this company transformed its approach to business metrics from a tangled web of spreadsheets and disparate data sources into a streamlined, transparent, and democratized process accessible to the entire organization.

We'll also demonstrate how business users, such as sales operations analysts and finance teams, were able to ask questions using natural language to perform ad-hoc analysis on the fly without relying on technical experts or complex queries.

By the end of this session, attendees will understand the value of having a central store of governed metrics and an integrated semantic layer, enabling self-service analytics, consistent metric definitions, and effective collaboration between data teams and business users.

In this session, we will demo and discuss the four central pillars of an enterprise strategy to realize true ""Gen-BI"" - the infusion of Gen-AI and LLMs into your business and decision intelligence capabilities.

        • Direct operations on any data source, accessible to any user 

        • Sophisticated request handling through the simplicity of conversational speech 

        • The 'Multi-LLM' strategy - to bring the right model for the right data set

        • Security so you can tap into Gen-AI without concern

Every organisation is facing retention challenges and fighting the war for talent, especially data teams (and data skills for the broader business). But you might be looking in the wrong place for solutions -- your valued people are already there, with the needed domain knowledge. Funded by the levy and harnessing the power of applied learning, professional apprenticeships across data, tech and AI can help tap into this pipeline ready to be upskilled and re-skilled. Whether serving internal stakeholders or external customers is your north star, building data capability across the organisation to inform your strategy and stay ahead of the competition is table stakes in today’s world.

Join Pedro and Louisa to explore:

How Laing O’Rourke plans to enhance workforce capability to underpin a data revolution that will enable comprehensive organisational transformation

Creating a thriving data culture to set your organisation up for continuous upskilling at scale

How to ensure you’re tying business value to your data strategy

Over the last decade, QuestDB has been at the forefront of handling time series data with a focus on speed and efficiency. In this talk, I’ll share practical insights from our experience serving thousands of users, highlighting what we’ve learned about building and maintaining a fast database that can ingest millions of events per second.

QuestDB, an open-source time series database, has traditionally relied on a custom-built, non-standard data storage format designed for performance. As we move forward, we’re actively developing its architecture to support open formats like Apache Parquet and Arrow, reflecting a broader industry shift. I’ll discuss the engineering challenges we’ve faced during this transition, the new possibilities it creates, and why these changes are crucial for the evolving database landscape.

Through live demos, I’ll showcase QuestDB’s performance in real-time data ingestion and queries, and demonstrate some of the features enabled by these new formats.

You are under relentless pressure to prepare for massive data growth, empower end users, and reduce application sprawl, all while building the infrastructure needed for AI adoption and securely sharing data across entities. The urgency to cut the overhead of delivering data products has never been greater, demanding a unified approach to these challenges.

See how Sigma and Sigma's customers have consolidated and even eliminated applications, built highly leveraged data products and, most importantly, put self-service data in the hands of everyone at the enterprise.

Maintaining customer loyalty has become increasingly difficult, causing organisations across all industries to revisit their customer-oriented decision-making by using data and technology that will ensure their customers' experiences drive business value. But where exactly should organisations start?

The key is through building cloud native data technology solutions and deploying bespoke segmentations that provide deep customer insights, so you can turn these insights into action.

In this session, CACI’s Director of Data Science, Richard Tomlinson, and Director of Data Technology, Jon Ede, will demonstrate how the winning combination of innate customer understanding, integrated technology and the power of data science is enabling leading organisations to put the customer at the heart of all decision-making across the organisation.

Data & AI are both powerful technologies and catalysts for organisational transformation, but both should be aligned with your business strategy - your 'why' - and their investment not be the end itself. In this session we will explore how data and AI capabilities align with strategic organisational goals and discuss five key value drivers in successful data and AI strategies that create the business case for investment. 

Join us as John Readman, Founder & Product owner of ASK BOSCO®, unveils how their cutting-edge AI Marketing Platform is revolutionising the industry with ThoughtSpot’s powerful TSE solution. From overcoming frustrating limitations with previous platforms to embracing AI for explosive growth, John will share their exciting journey and vision. Don’t miss this chance to see how ASK BOSCO® is setting new standards and why ThoughtSpot is their game-changer. Be part of this transformative session and witness the future of analytics in action! John will be joined by Cindi Howson Chief Data Strategy Officer at ThoughtSpot and Host of award winning The Data Chief podcast.

Data quality issues due to lack of clear data definition ». Example of unclear surface areas definitions.

• Solution: Set up data governance & organization to support it. Implement a data catalog & the choice of DataGalaxy
• Results: Data Catalog usage within Cofinimmo. Efficiency gains and risk reduction thanks to clear data definitions and data quality improvement.

The success of AI initiatives hinges on DATA. According to recent research, only 10% of enterprises will achieve the expected ROI from their Generative AI deployments, with data quality issues being the most cited reason for failure. The core message is clear: 'You are as AI-ready as your data.' This session will explore practical approaches to overcoming common data challenges and ensuring your data meets the specific requirements of AI techniques.

Key Takeaways:

• Understanding AI Readiness & how to assess it?

• AI-Ready Data: Two core Foundations

• Build a scalable data infrastructure that accelerates AI deployment and innovation. DQLabs Framework & Practical Approaches to fix your data problems.

In a world where speed and precision are paramount, DirectlyApply harnesses the power of real-time AI to revolutionise the job search experience. Join Dylan Buckley, CTO and co-founder, as he explores how DirectlyApply’s innovative use of SingleStore’s data platform has driven a 10x boost in user engagement by delivering ultra personalised job matches with unparalleled speed and accuracy, increasing application success — delighting both job seekers and employers.

Learn about SQLMesh, an open source data transformation tool that addresses the pain points that your data practitioners experience daily.

A 30 minute demo of how to use Redpanda Connect (powered by Benthos) to generate vector embeddings on streaming text. This session will walk through the architecture and configuration used to seamlessly integrate Redpanda Connect with LangChain, OpenAI, and MongoDB Atlas to build a complete Retrieval Augmented Generation data pipeline.

In today's data-driven landscape, the ability to efficiently harness the power of AI is crucial for businesses seeking to unlock valuable insights and drive innovation. This session will explore how BigQuery, Google Cloud's leading data warehouse solution, can accelerate your AI initiatives. Discover how BigQuery's serverless architecture, built-in machine learning capabilities, and seamless integration with Google Cloud's AI ecosystem empower you to build, train, and deploy ML models at scale. Whether you're a data scientist, engineer, or business leader, this session will provide you with actionable insights and strategies to supercharge your AI efforts with BigQuery.

In the next five years, we are poised to witness a significant transformation towards modern data lake architecture across industries. This shift is driven by an urgent need for a unified, flexible, and scalable data management solution. Such a solution must address the challenges of siloed data environments and the increasing complexity of data sources while balancing the benefits of data mesh principles with centralized governance and semantic consistency.

In this talk, we will cover latest trends and benefits in this field, as well as usage of open formats like Iceberg, lower costs of data movement, & multiple engines to support different workloads that ultimately helps in getting into a single source of truth.

As technology evolves and organizations shift from digital to AI-native, data becomes the cornerstone of innovation. AI both relies and thrives on data, transforming raw information into valuable insights. This session explores how empathy—through trust and openness—plays a crucial role in creating resilient data, analytics, and AI platforms. Join us to examine emerging trends and technologies that can unlock the full potential of your data. We will discover why embracing empathy in your technological infrastructure fosters more adaptable, reliable, and effective data-driven solutions. Additionally, you'll learn how your technological infrastructure can ensure a stronger path to success in the AI era.

Condé Nast is one of the world's most renowned media companies that creates and distributes content with a footprint of over 1 billion consumers in 32 territories through print, digital, video, and social platforms. At the heart of Condé Nast is data to better understand and delight our customers. The company’s data governance experts play a critical role in maintaining the highest quality of content and ensuring data integrity, security, and accessibility while optimizing consumer engagement. Condé Nast's data culture promotes and measures data governance alongside data search and discovery, enables data leadership, and focuses strongly on data literacy to maximize return on investment for data programs. Learn from data governance expert, Hilda Sadek, on what it takes to build a transformative, high-growth data culture using data governance.

Artificial Intelligence (AI) has become a strategic imperative in a rapidly evolving business landscape. However, the rush to embrace AI comes with risks, as illustrated by instances of AI-generated content with fake citations and potentially dangerous recommendations. The critical factor underpinning trustworthy AI is data integrity, ensuring data is accurate, consistent, and full of rich context.

If doubts about data integrity are slowing down AI projects in your organisation, join this session where Precisely and Generali will share real-world successes and the three critical factors you must address to ensure that your data minimises AI bias and hallucination while producing nuanced, coherent, and contextually relevant responses.

During this presentation you will:

• Understand the impacts around delivering data that is not AI-ready.

• Hear real world considerations in bringing accuracy, consistency, and relevance to your AI models.

• Uncover practical solutions to common AI challenges such as AI bias, and lack of contextual relevance.