AI Governance addresses the safe and transparent deployment of artificial intelligence solutions. Join AI Risk Leader Avishay Gaziel and Adrian Estala, Field CDO, as they weigh the tradeoffs and introduce the concept of data products as an approach for bringing in secure and quality data into AI engines.

In the next episode of Starburst TV with Adrian Estala, we tackle Knowledge Graphs with the host of Catalogs and Cocktails, and Principal Scientist & Head of AI Lab at data.world. Following Juan Sequeda's “No BS” approach, we will discuss why knowledge graphs are such an important capability for building business intelligence across your enterprise data.

Join us on the next episode of StarburstTV where Adrian Estala will discuss the fascinating topic of game theory in data analytics. You don't need two PhD's to enjoy the show as we will talk about strategy and application with a leading data innovator, Gerardo Parrello

In today’s innovative data landscape, achieving business outcomes still hinges upon the same pillars of data quality, regulatory compliance, and business enablement. Balancing your data governance approach with the speed and analytics driven value that your business teams demand is challenging. A modern data strategy requires governance to be as agile and innovative as the AI solutions that are being developed. Next up on Starburst TV, we join Slalom’s Senior Director, Alfredo Bird-Munoz and Field CDO Adrian Estala as they explore the reciprocal relationship between AI and data governance: the influence of AI on ensuring the integrity of data fed into models, and conversely, the role of governance in AI deployment and utilization of its outputs.

Field CDO, Adrian Estala delves into GigaOm's new report findings that challenge the cloud data warehouses position in a truly modern data stack. The report presents an alternative — one that offers lower cost and increases flexibility to run fast analytics on all your data, while significantly reducing complexity and data movement. Gain valuable insights from guest speakers Lutz Künneke, Director of Engineering, and Isa I., Senior Data Engineer, representing BestSecret, as they share their journey from Snowflake to Starburst Trino and Iceberg. Concluding the discussion, Justin Borgman, Co-Founder & CEO of Starburst, offers a fresh perspective on the modern data stack, revealing its hidden limitations.

The transition to a modern data platform is crucial for many organizations — for their competitiveness and growth. Hear from Abhishek Nahar, Data Platform & Products Leader at Asurion and Starburst’s Adrian Estala, Field CDO about their personal viewpoints on what it means for them to from a legacy architecture to an agile data platform. Learning from their experience and other data professionals, it involves strategic decisions and a shift from a monolithic central engineering function to an agile, hybrid business-IT model. Data products also play a key role, empowering autonomous product teams to create and manage their solutions, all leveraging the same core platform. Looking ahead, the future holds immense potential, with advanced analytics, AI, and data partnerships driving further growth and transformation.

While Trino is mostly known for ad-hoc analytics, companies like Salesforce and Lyft were using Trino to run long-running queries at a petabyte scale. With the implementation of fault-tolerant execution, running those queries becomes even easier. Learn about the architecture behind the feature which makes this possible and the potential capabilities it can bring to your own ecosystem.

7bridges is an AI-powered logistical supply chains platform and was named one of the top 15 hottest AI startups in Europe in 2020. Hear from Simon Thelin, lead data engineer, about how this fast growing company is using Starburst Galaxy to power reporting and AI

Let’s put theory into practice. Listen to Simone Grandi, Glovo’s Data Platform Engineering Manager, discuss their experience implementing data mesh firsthand. Hear about their organizational challenges, future strategies, and interest in data as a product. We’ll then watch Vishal Singh, Head of Data Products at Starburst, use Starburst Data Products to demonstrate a quick and easy way to get started with setting up and running a data mesh in your organization.

Best-selling author Joe Reis debates the benefits and pitfalls of the Data Mesh for Data Engineers. Is data mesh the pinnacle of data engineering innovation, or will it challenge data engineering as we know it? Maybe both? Join Joe Reis, best-selling author of Fundamentals of Data Engineering, along with Starburst technical experts, Colleen Tartow and Andy Mott, for a fun and lively Oxford style debate on whether the adoption of Data Mesh creates opportunity or spells doom for the field of Data Engineering.

Being a startup founder requires a special blend of ambition, drive, and resilience. Not only does the role demand grit, it also calls for the ability to dream. Hear the unique perspective from founders in the data space, Matt Fuller from Starburst, Drew Banin from dbt, Max Beauchemin from Preset, and Michel Tricot from Airbyte. Listen as our star studded founder panel takes part in an open discussion about the future of data platforms, the importance of open source, the ecosystem, and paying attention to user experience.

As data architectures evolve there is a big question to answer: How do we best evolve people, too? Is it more pragmatic to adopt a “Modern Data Stack” which is iterative and requires less people and process change? Is it better to take a more holistic approach, which Data Mesh proposes, pushing people & technology forward at once? What is the best next step toward companies becoming data-driven? This fireside chat, moderated by Justin Borgman, Starburst Co-Founder & CEO, will bring the stars of the data world to the table to discuss the hard and soft side of data: People and technology.

With its hybrid data architecture, Starburst provides the fastest, most efficient analytics engine for data warehouses, data lakes, or data mesh. How can you take that innovation and accelerate time to value further? Partner with industry leader, Dell Technologies to help customers overcome the challenge of data silos across their Multicloud environment spanning public cloud, private cloud and on-premises. Join to learn how Dell Technologies and Starburst are helping IT and data leaders address the data challenges of multicloud era to accelerate time to value.

In this fireside chat, Michelle Boston, Managing Director of Data Management Technology, and Amy Avery, Senior Vice President and Head of Analytics, Research & Insights, will discuss the collaboration between their teams at Bank of America to drive business forward through the analysis of critical data while maintaining data security and governance. The conversation will be moderated by Cindi Howson, host of The Data Chief Podcast and CDSO at ThoughtSpot. This keynote will provide insights on how to achieve faster analytics and broader data usage while prioritizing data security.

Environment, Social, and Corporate Governance (ESG) goals have grown from aspirational ideas to business imperatives. Not only is it the right thing to do to help protect our planet, but ESG initiatives are also increasingly regulated. On the Datanova stage, Dan O’Riordan, VP – Global Head of Platform & AI Engineering at Capgemini, will explore: How can your data strategy reduce your carbon footprint? Might there be a path to identifying opportunities to hit your ESG targets by building data products that help reduce waste and carbon emissions, while improving supply chains? The concept of data products means local responsibility on quality. This will include relevant data elements such as green energy use and waste. Further, future data ecosystems will need to be collaboratively built on a foundation of sustainable, conscious data products.

The way we have been building analytics takes too long, incurs high costs and often only partially meets business requirements. Data products provide a way out of this mess. But to build data products efficiently, a cohesive mindset is needed. One where the key elements comprising data quality, data governance, DataOps, observability, and data security become equal first citizens. This session delves into how data and analytics teams are helping successful organizations get the most out of their data assets.

Organizations of all sizes strive to proclaim the badge of honor that their company is “data-driven.” No decision should be made without the corroborative analysis to support the answered question causing the decision, but what if your business is asking the wrong questions? It is common for data consumers to toss idealistic requirements over the fence without understanding the data sources at large, as this responsibility falls to the data engineer who works with the data daily. To transition from data to information, data engineers must cultivate a habit of acting as curious challengers on behalf of the data they are working with and be given the power of a stakeholder within the data manipulation process.