At Nubank, we successfully migrated to Unity Catalog, addressing the needs of our large-scale data environment with 3k active users, over 4k notebooks and jobs and 1.1 million tables, including sensitive PII data. Our primary objectives were to enhance data governance, security and user experience.Key points: Comprehensive data access monitoring and control implementation Enhanced security measures for handling PII and sensitive data Efficient migration of 4,000+ notebooks and jobs to the new system Improved cataloging and governance for 1.1 million tables Implementation of robust access controls and permissions model Optimized user experience and productivity through centralized data management This migration significantly improved our data governance capabilities, enhanced security measures and provided a more user-friendly experience for our large user base, ultimately leading to better control and utilization of our vast data resources.

Atlassian is rebuilding its central lakehouse from the ground up to deliver a more secure, flexible and scalable data environment. In this session, we’ll share how we leverage Unity Catalog for fine-grained governance and supplement it with Immuta for dynamic policy management, enabling row and column level security at scale. By shifting away from broad, monolithic access controls toward a modern, agile solution, we’re empowering teams to securely collaborate on sensitive data without sacrificing performance or usability. Join us for an inside look at our end-to-end policy architecture, from how data owners declare metadata and author policies to the seamless application of access rules across the platform. We’ll also discuss lessons learned on streamlining data governance, ensuring compliance, and improving user adoption. Whether you’re a data architect, engineer or leader, walk away with actionable strategies to simplify and strengthen your own governance and access practices.

Struggling to keep up with data governance at scale? Join us to explore how automated data classification, tag policies and ABAC streamline access control while enhancing security and compliance. Get an exclusive look at the new Governance Hub, built to give your teams deeper visibility into data usage, access patterns and metadata — all in one place. Whether you're managing thousands or millions of assets, discover how to classify, tag and protect your data estate effortlessly with the latest advancements in Unity Catalog.

Given that data is the new oil, it must be treated as such. Organizations that pursue greater insight into their businesses and their customers must manage, govern, protect and observe the use of the data that drives these insights in an efficient, cost-effective, compliant and auditable manner without degrading access to that data. Azure Data Lake Storage offers many features which allow customers to apply such controls and protections to their critical data assets. Understanding how these features behave, the granularity, cost and scale implications and the degree of control or protection that they apply are essential to implement a data lake that reflects the value contained within. In this session, the various data protection, governance and management capabilities available now and upcoming in ADLS will be discussed. This will include how deep integration with Azure Databricks can provide a more comprehensive, end-to-end coverage for these concerns, yielding a highly efficient and effective data governance solution.

Deloitte and GM (General Motors) Financial have collaborated to design and implement a cutting-edge cloud analytics platform, leveraging Databricks. In this session, we will explore how we overcame challenges including dispersed and limited data capabilities, high-cost hardware and outdated software, with a strategic and comprehensive approach. With the help of Deloitte and Databricks, we were able to develop a unified Customer360 view, integrate advanced AI-driven analytics, and establish robust data governance and cyber security measures. Attendees will gain valuable insights into the benefits realized, such as cost savings, enhanced customer experiences, and broad employee upskilling opportunities. Unlock the impact of cloud data modernization and advanced analytics in the automotive finance industry and beyond with Deloitte and Databricks.

In today's rapidly evolving digital landscape, organizations must prioritize robust data architectures and AI strategies to remain competitive. In this session, we will explore how Procter & Gamble (P&G) has embarked on a transformative journey to digitize its operations via scalable data, analytics and AI platforms, establishing a strong foundation for data-driven decision-making and the emergence of agentic AI.Join us as we delve into the comprehensive architecture and platform initiatives undertaken at P&G to create scalable and agile data platforms unleashing BI/AI value. We will discuss our approach to implementing data governance and semantics, ensuring data integrity and accessibility across the organization. By leveraging advanced analytics and Business Intelligence (BI) tools, we will illustrate how P&G harnesses data to generate actionable insights at scale, all while maintaining security and speed.

In the contemporary landscape of data management, organizations are increasingly faced with the challenges of data segregation, governance and permission management, particularly when operating within complex structures such as holding companies with multiple subsidiaries. Unipol comprises seven subsidiary companies, each with a diverse array of workgroups, leading to a cumulative total of multiple operational groups. This intricate organizational structure necessitates a meticulous approach to data management, particularly regarding the segregation of data and the assignment of precise read-and-write permissions tailored to each workgroup. The challenge lies in ensuring that sensitive data remains protected while enabling seamless access for authorized users. This speech wants to demonstrate how Unity Catalog emerges as a pivotal tool in the daily use of the data platform, offering a unified governance solution that supports data management across diverse AWS environments.

You shouldn’t have to sacrifice data governance just to leverage the tools your business needs. In this session, we will give practical tips on how you can cut through the data sprawl and get a unified view of your data estate in Unity Catalog without disrupting existing workloads. We will walk through how to set up federation with Glue, Hive Metastore, and other catalogs like Snowflake, and show you how powerful new tools help you adopt Databricks at your own pace with no downtime and full interoperability.

In this course, you'll learn concepts and perform labs that showcase workflows using Unity Catalog - Databricks' unified and open governance solution for data and AI. We'll start off with a brief introduction to Unity Catalog, discuss fundamental data governance concepts, and then dive into a variety of topics including using Unity Catalog for data access control, managing external storage and tables, data segregation, and more. Pre-requisites: Beginner familiarity with the Databricks Data Intelligence Platform (selecting clusters, navigating the Workspace, executing notebooks), cloud computing concepts (virtual machines, object storage, etc.), production experience working with data warehouses and data lakes, intermediate experience with basic SQL concepts (select, filter, groupby, join, etc), beginner programming experience with Python (syntax, conditions, loops, functions), beginner programming experience with the Spark DataFrame API (Configure DataFrameReader and DataFrameWriter to read and write data, Express query transformations using DataFrame methods and Column expressions, etc.) Labs: Yes Certification Path: Databricks Certified Data Engineer Associate

In this course, you’ll learn how to apply patterns to securely store and delete personal information for data governance and compliance on the Data Intelligence Platform. We’ll cover topics like storing sensitive data appropriately to simplify granting access and processing deletes, processing deletes to ensure compliance with the right to be forgotten, performing data masking, and configuring fine-grained access control to configure appropriate privileges to sensitive data.Pre-requisites: Ability to perform basic code development tasks using the Databricks workspace (create clusters, run code in notebooks, use basic notebook operations, import repos from git, etc), intermediate programming experience with SQL and PySpark (extract data from a variety of file formats and data sources, apply a number of common transformations to clean data, reshape and manipulate complex data using advanced built-in functions), intermediate programming experience with Delta Lake (create tables, perform complete and incremental updates, compact files, restore previous versions etc.). Beginner experience with Lakeflow Declarative Pipelines and streaming workloads.Labs: YesCertification Path: Databricks Certified Data Engineer Professional

Retrieval Augmented Generation (RAG) continues to be a foundational approach in AI despite claims of its demise. While some marketing narratives suggest RAG is being replaced by fine-tuning or long context windows, these technologies are actually complementary rather than competitive. But how do you build a truly effective RAG system that delivers accurate results in high-stakes environments? What separates a basic RAG implementation from an enterprise-grade solution that can handle complex queries across disparate data sources? And with the rise of AI agents, how will RAG evolve to support more dynamic reasoning capabilities? Douwe Kiela is the CEO and co-founder of Contextual AI, a company at the forefront of next-generation language model development. He also serves as an Adjunct Professor in Symbolic Systems at Stanford University, where he contributes to advancing the theoretical and practical understanding of AI systems. Before founding Contextual AI, Douwe was the Head of Research at Hugging Face, where he led groundbreaking efforts in natural language processing and machine learning. Prior to that, he was a Research Scientist and Research Lead at Meta’s FAIR (Fundamental AI Research) team, where he played a pivotal role in developing Retrieval-Augmented Generation (RAG)—a paradigm-shifting innovation in AI that combines retrieval systems with generative models for more grounded and contextually aware responses. In the episode, Richie and Douwe explore the misconceptions around the death of Retrieval Augmented Generation (RAG), the evolution to RAG 2.0, its applications in high-stakes industries, the importance of metadata and entitlements in data governance, the potential of agentic systems in enterprise settings, and much more. Links Mentioned in the Show: Contextual AIConnect with DouweCourse: Retrieval Augmented Generation (RAG) with LangChainRelated Episode: High Performance Generative AI Applications with Ram Sriharsha, CTO at PineconeRegister for RADAR AI - June 26 New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Organizations struggle to make sense of numerous programs and projects that overlap or operate in silos. This research will weave together data and analytics governance, MDM and data quality into one organized initiative that every CDAO should be interested in.

Legacy systems slow organisations due to scale limits, risk, and cost. In this session, we will walkthrough how enterprises use Archon Data Store, our AI-powered archival platform, to create enterprise-wide data archival strategies for their legacy and modern data. Through use cases from finance, pharma and manufacturing - we will learn intelligent archival techniques that enable organisations to discover their data; align their past, present and future data footprint through decommissioning and migration while enhancing system performance, security and stewardship for their enterprise data.

Productivity and operational efficiency are one of the key measures of business performance and economics. GenAI has promising capabilities of improving productivity and operational efficiency of data management function, and data governance. Organizations should explore and assess those capabilities to align it with strategic goals to improve the productivity and operational efficiency.

Organizations today require more than dashboards—they need applications that combine insights with data collection and action capabilities to drive meaningful change. In this session, Stipo Josipovic (Director of Product) will showcase the key innovations enabling this shift, from expanded write-back capabilities to workflow automation features.

You'll learn about Sigma's growing data app capabilities, including:

Enhanced write-back features: Redshift and upcoming BigQuery support, bulk data entry, and form-based collection for structured workflows Advanced security controls: Conditional editing and row-level security for precise data governance Intuitive interface components: Containers, modals, and tabbed navigation for app-like experiences Powerful Actions framework: API integrations, notifications, and automated triggers to drive business processes This session covers both recently released features and Sigma's upcoming roadmap, including detail views, simplified form-building, and new API actions to integrate with your tech stack. Discover how Sigma helps organizations move beyond analysis to meaningful action.

➡️ Learn more about Data Apps: https://www.sigmacomputing.com/product/data-applications?utm_source=youtube&utm_medium=organic&utm_campaign=data_apps_conference&utm_content=pp_data_apps

➡️ Sign up for your free trial: https://www.sigmacomputing.com/go/free-trial?utm_source=youtube&utm_medium=video&utm_campaign=free_trial&utm_content=free_trial

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This primary goal of this workshop is to equip participants with strategies and practical techniques to secure enterprisewide support for data governance initiatives. The workshop focuses on building a compelling business case, engaging key stakeholders and demonstrating the value of data governance to the organization.

As we enter a new era of productivity, automation isn’t about armies of robots—it’s about enabling better decisions through algorithms. For knowledge workers, the true transformation is human-centric.
While generative AI and robotics capture headlines, the real foundation of successful automation is high-quality, well-governed data. Without it, your AI initiatives will stall, and your brand could suffer.
Join Soda and LexisNexis Risk Solutions to explore how empowering your people with data governance, observability, and literacy is the key to unlocking the full potential of agents and GenAI.

Power BI and Microsoft Fabric have become the data hub for your organisation, providing everyone access to your critical and sensitive data. Whilst incredibly powerful, this also brings significant risk.
Including real world case studies, this session will look at how you can protect your organisation, your data, and yourself, through effective governance, auditing and disaster recovery within Power BI and Fabric.
This will cover effective planning, risk management, license reduction, FinOps, permissions monitoring, audit trails, and more.

In this exclusive session, we’ll explore how the London Stock Exchange Group (LSEG) is transforming its data governance journey with Solidatus, placing data lineage at the core. With its history dating back more than 300 years, LSEG’s complex data landscape has been shaped by acquisitions and historic systems, which presents unique challenges in mapping data flows across diverse technology stacks. Learn how LSEG is partnering with Solidatus to overcome governance challenges, achieve regulatory compliance, and why data lineage is essential for building trust in data products.

This session will delve into the critical role that emotional intelligence (EQ) plays in the successful implementation of data governance frameworks. It will explore how EQ can enhance collaboration, communication and compliance among stakeholders, ultimately leading to more effective data governance.