Women in AI experts will provide a unique perspective on why it is important to start with the data for algorithms to be ethical, be it for new transformations or for enterprise transitions towards the Generative AI era. Data governance along with regulatory audits are not sufficient anymore, and the multifaceted responsibilities towards an accessible and inclusive future for all humans requires a comprehensive data strategy. The panelists will share industry perspectives from finance and sustainability that emphasize privacy, security, synthetic data, and maturity scores to scale ethical models.

Step into the dynamic world of data governance, business operations, and artificial intelligence (AI), where the unsung hero—metadata—takes center stage. Just like the perfect sandwich relies on clear definitions of its ingredients, this talk unveils the indispensable role of metadata in defining and organizing data.

George will share captivating real-life stories and examples on how clarity in definitions and metadata not only streamlines operations but also empowers decision-makers with invaluable insights.

Explore the backbone of AI advancement through essential data management tools: the Business Glossary, Data Dictionary, Data Catalog, and Machine Learning Metadata Store. Let's embark on a journey where unified interpretations pave the way for accuracy, efficiency, and success in the data-driven era.

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. 

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!

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.

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.

As AI adoption continues to grow at a rapid pace, data governance will become critical to ensure high-quality data powers AI models and large language models. Learn about the newest data governance innovations for Dataplex, including new integrations with Vertex AI, to help enterprises centrally discover, manage, monitor, and govern data across all data types to power analytics and AI at scale. Learn from leaders at Orange and Ford on how they are leveraging Dataplex to securely manage and govern their data in the AI era.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

When data is the most valuable asset of your company, protecting it is a non-negotiable. While Information Security professionals are focused on Bad Actors, we have data operations and data governance professionals focused on Bad Data… Are they one and the same? What’s similar and what’s different between the worlds of data integrity and data security?

Drawing from a wealth of experience and real-world challenges, Gorkem will shed light on the pivotal role of data quality in the forefront of information security. We’ll discuss opportunities for early detection, auto-detection, and the establishment of tiered rules to manage and remediate bad data effectively. Learn how proactive governance and observability can transform data management from a reactive stance to a formidable defense mechanism, ensuring the integrity and security of your data ecosystem. 

In today's data-driven world, organizations face the challenge of not only harnessing the power of data but also ensuring its responsible and effective use. This panel discussion will delve into the critical components of embedding data governance and data literacy into the fabric of organizational culture. Data governance forms the foundation of a robust data strategy, encompassing policies, processes, and frameworks to ensure data quality, integrity, and security. However, effective governance requires more than just frameworks; it necessitates a cultural shift where data stewardship is ingrained into every aspect of organizational operations. Moreover, data literacy is paramount in enabling individuals across an organization to effectively interpret, analyze, and derive insights from data. By cultivating a culture of data literacy, organizations empower employees to make informed decisions, driving innovation and growth. This panel will explore strategies for fostering a culture of accountability, collaboration, and trust around data practices driving sustainable success in today's dynamic business landscape.

Slow query engines are forcing users to copy data from open data lakehouses into proprietary data warehouses to achieve their desired performance, but this results in a complex, costly ingestion pipeline that undermines data governance. In this talk, we will dive into the latest developments in data lakehouse querying, why you should avoid using proprietary data warehouses for accelerating queries, and how enterprises like Trip.com are unifying their SQL workloads directly on open data lakehouses.

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.

Data is the linchpin of competitive advantage. This session takes you on a deep dive into the revolutionary best practices of enterprise AI data pipelines. We'll unpack the complexities of data integration from multiple silos, orchestrating data to GPUs, and building fast and efficient infrastructure for AI. We'll explore innovative strategies for data governance, real-time processing, and seamless orchestration across disparate systems.

Learn how industry leaders are leveraging these practices to drive decision-making, enhance customer experiences, and catalyze digital transformation. Join us to empower your enterprise with the architecture that will lead tomorrow's Enterprise AI landscape, and walk away with a practical blueprint for constructing resilient, scalable, and efficient Enterprise AI architectures.

Driving trust with data is essential to succeeding with analytics. However, time and time again, data quality remains an issue for most organizations today. In this session, Esther Munyi, Chief Data Officer at Sasfin, Amy Grace, Director, Military Engines Digital Strategy at Pratt & Whitney, Stefaan Verhulst, Chief Research & Development Officer, Director of Data Program at NYU Governance Lab, and Malarvizhi Veerappan, Program Manager and Senior Data Scientist at the World Bank will focus on strategies for improving data quality, fostering a culture of trust around data, and balancing robust governance with the need for accessible, high-quality data.

Discover how to implement a modern data mesh architecture using Microsoft Azure's Cloud Adoption Framework. In this book, you'll learn the strategies to decentralize data while maintaining strong governance, turning your current analytics struggles into scalable and streamlined processes. Unlock the potential of data mesh to achieve advanced and democratized analytics platforms. What this Book will help me do Learn to decentralize data governance and integrate data domains effectively. Master strategies for building and implementing data contracts suited to your organization's needs. Explore how to design a landing zone for a data mesh using Azure's Cloud Adoption Framework. Understand how to apply key architecture patterns for analytics, including AI and machine learning. Gain the knowledge to scale analytics frameworks using modern cloud-based platforms. Author(s) None Deswandikar is a seasoned data architect with extensive experience in implementing cutting-edge data solutions in the cloud. With a passion for simplifying complex data strategies, None brings real-world customer experiences into practical guidance. This book reflects None's dedication to helping organizations achieve their data goals with clarity and effectiveness. Who is it for? This book is ideal for chief data officers, data architects, and engineers seeking to transform data analytics frameworks to accommodate advanced workloads. Especially useful for professionals aiming to implement cloud-based data mesh solutions, it assumes familiarity with centralized data systems, data lakes, and data integration techniques. If modernizing your organization's data strategy appeals to you, this book is for you.

There is a concept in software engineering which is called ‘shifting left’, this focuses on testing software a lot earlier in the development lifecycle than you would normally expect it to. This helps teams building the software create better rituals and processes, while also ensuring quality and usability are key aspects to evaluate as the software is being built. We know this works in software development, but what happens when these practices are used when building AI tools? Saurabh Gupta is a seasoned technology executive and is currently Chief Strategy & Revenue Officer The Modern Data Company. With over 25 years of experience in tech, data and strategy, he has led many strategy and modernization initiatives across industries and disciplines. Through his career, he has worked with various Internation Organizations and NGOs, Public sector and Private sector organizations. Before joining TMDC, he was the Head of Data Strategy & Governance at ThoughtWorks & CDO/Director for Washington DC Gov., where he developed the digital/data modernization strategy for education data. Prior to DCGov he played leadership and strategic roles at organizations including IMF and World Bank where he was responsible for their Data strategy and led the OpenData initiatives. He has also closely worked with African Development Bank, OECD, EuroStat, ECB, UN and FAO as a part of inter-organization working groups on data and development goals. As a part of the taskforce for international data cooperation under the G20 Data Gaps initiative, he chaired the technical working group on data standards and exchange. He also played an advisor role to the African Development Bank on their data democratization efforts under the Africa Information Highway. In the episode, Adel & Saurabh explore the importance of data quality and how ‘shifting left’ can improve data quality practices, the role of data governance, the emergence of data product managers, operationalizing ‘shift left’ strategies through collaboration and data governance, the challenges faced when implementing data governance, future trends in data quality and governance, and much more.  Links Mentioned in the Show: The Modern Data CompanyMonte Carlo: The Annual State of Data Quality Survey[Course] Data Governance Concepts[Webinar] Crafting a Lean and Effective Data Governance Strategy Related Episode: Building Trust in Data with Data Governance New to DataCamp? Learn on the go using the DataCamp mobile app Empower your business with world-class data and AI skills with DataCamp for business

Despite the critical role of analytics in guiding business decisions, organizations continue to face significant challenges in harnessing its full potential. As data sets expand and deadlines shrink, the urgency to scale analytics processes becomes paramount. What data leaders now need to focus on are essential strategies for analytics at scale, including fostering a culture of continuous learning, prioritizing data governance, and leveraging generative AI. Libby Duane Adams is the Chief Advocacy Officer and co-founder of Alteryx. She is responsible for strengthening upskilling and reskilling efforts for Alteryx customers to enable a culture of analytics, scaling the presence of the Alteryx SparkED education program and furthering diversity and inclusion in the workplace. As the former Chief Customer Officer, Libby has helped many Fortune 100 executives to identify and seize market opportunities, outsmart their competitors, and drive more revenue from their current businesses using analytics.  In the episode, Richie and Libby explore the differences between analytics and business intelligence, analytics as a team sport, the importance of speed in analytics, generative AI and its implications in analytics, the role of data quality and governance, Alteryx’s AI platform, data skills as a workplace necessity, using AI to automate documentation and insights, success stories and mistakes within analytics, and much more.  Links Mentioned in the Show: AlteryxAlteryx SparkED Program[Course] Introduction to AlteryxRelated Episode: From Data Literacy to AI Literacy with Cindi Howson, Chief Data Strategy Officer at ThoughtSpotSign up to RADAR: The Analytics Edition 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

With the increasing adoption of Generative AI, learn how data governance will add value to and benefit from Generative AI. Published at: https://www.eckerson.com/articles/data-governance-in-the-era-of-generative-ai

Databricks started out as a platform for using Spark, a big data analytics engine, but it's grown a lot since then. Databricks now allows users to leverage their data and AI projects in the same place, ensuring ease of use and consistency across operations. The Databricks platform is converging on the idea of data intelligence, but what does this mean, how will it help data teams and organizations, and where does AI fit in the picture? Ari is Databricks’ Head of Evangelism and "The Real Moneyball Guy" - the popular movie was partly based on his analytical innovations in Major League Baseball. He is a leading influencer in analytics, artificial intelligence, data science, and high-growth business innovation. Ari was previously the Global AI Evangelist at DataRobot, Nielsen’s regional VP of Analytics, Caltech Alumni of the Decade, President Emeritus of the worldwide Independent Oracle Users Group, on Intel’s AI Board of Advisors, Sports Illustrated Top Ten GM Candidate, an IBM Watson Celebrity Data Scientist, and on the Crain’s Chicago 40 Under 40. He's also written 5 books on analytics, databases, and baseball. Robin is the Field CTO at Databricks. She has consulted with hundreds of organizations on data strategy, data culture, and building diverse data teams. Robin has had an eclectic career path in technical and business functions with more than two decades in tech companies, including Microsoft and Databricks. She also has achieved multiple academic accomplishments from her juris doctorate to a masters in law to engineering leadership. From her first technical role as an entry-level consumer support engineer to her current role in the C-Suite, Robin supports creating an inclusive workplace and is the current co-chair of Women in Data Safety Committee. She was also recognized in 2023 as a Top 20 Women in Data and Tech, as well as DataIQ 100 Most Influential People in Data. In the episode, Richie, Ari, and Robin explore Databricks, the application of generative AI in improving services operations and providing data insights, data intelligence, and lakehouse technology, the wide-ranging applications of generative AI, how AI tools are changing data democratization, the challenges of data governance and management and how tools like Databricks can help, how jobs in data and AI are changing and much more.  About the AI and the Modern Data Stack DataFramed Series This week we’re releasing 4 episodes focused on how AI is changing the modern data stack and the analytics profession at large. The modern data stack is often an ambiguous and all-encompassing term, so we intentionally wanted to cover the impact of AI on the modern data stack from different angles. Here’s what you can expect: Why the Future of AI in Data will be Weird with Benn Stancil, CTO at Mode & Field CTO at ThoughtSpot — Covering how AI will change analytics workflows and tools How Databricks is Transforming Data Warehousing and AI with Ari Kaplan, Head Evangelist & Robin Sutara, Field CTO at Databricks — Covering Databricks, data intelligence and how AI tools are changing data democratizationAdding AI to the Data Warehouse with Sridhar Ramaswamy, CEO at Snowflake — Covering Snowflake and its uses, how generative AI is changing the attitudes of leaders towards data, and how to improve your data managementAccelerating AI Workflows with Nuri Cankaya, VP of AI Marketing & La Tiffaney Santucci, AI Marketing Director at Intel — Covering AI’s impact on marketing analytics, how AI is being integrated into existing products, and the democratization of AI Links Mentioned in the Show: DatabricksDelta Lakea href="https://mlflow.org/" rel="noopener...

Conventional data governance conflicts with today’s world of self-service analytics and agile projects. Published at: https://www.eckerson.com/articles/modern-data-governance-problems