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DataFramed

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Welcome to DataFramed, a weekly podcast exploring how artificial intelligence and data are changing the world around us. On this show, we invite data & AI leaders at the forefront of the data revolution to share their insights and experiences into how they lead the charge in this era of AI. Whether you're a beginner looking to gain insights into a career in data & AI, a practitioner needing to stay up-to-date on the latest tools and trends, or a leader looking to transform how your organization uses data & AI, there's something here for everyone.

Join co-hosts Adel Nehme and Richie Cotton as they delve into the stories and ideas that are shaping the future of data. Subscribe to the show and tune in to the latest episode on the feed below.
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We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here.AI adoption is not just about flashy innovations or big models. For businesses, it’s about solving real problems and driving measurable outcomes. That means aligning your data infrastructure, navigating compute costs, and understanding where AI adds the most value. How do enterprises prioritize their use cases? What role does hybrid play in scaling securely and efficiently? What’s the next frontier beyond generative AI?As Chief Strategy Officer, Abhas Ricky leads the overall corporate strategy for Cloudera and is responsible for creating the company vision, building the business and customer target operating model, communicating that with key stakeholders via clearly defined OKRs, and executing key transformational initiatives to realize that plan. He’s also tasked with driving growth and innovation and making appropriate build/buy partner decisions, including pricing and packaging, corporate development, and Cloudera’s innovation accelerator to launch new products. Previously, he served as chief of staff and vice president for business transformation at the company. Prior to the Cloudera/Hortonworks merger, he helped scale Hortonworks’ go-to-market efforts as global head of customer innovation and value management. A management consultant by training, he is passionate about driving action and change in the society and has led projects with multiple organizations including the World Economic Forum, Founders of the Future, and other nonprofits. In the episode, Richie and Abhas explore the evolving landscape of data security and governance, the importance of data as an asset, the role of AI in transforming business processes, the challenges of data sprawl, and the significance of hybrid AI solutions, and much more.Links Mentioned in the Show:ClouderaConnect with AbhasCourse: Understanding Cloud Computing CourseRelated Episode: Aligning AI with Enterprise Strategy with Leon Gordon, CEO at Onyx DataRewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
Welcome to DataFramed Industry Roundups! In this series of episodes, Adel & Richie sit down to discuss the latest and greatest in data & AI. In this episode, we touch upon AI agents for data work, will the full-stack data scientist make a return, old languages making a comeback, Python's increase in performance, what they're both thankful for, and much more. Links Mentioned in the ShowFractal’s Data Science Agent: AryaArticle: What Makes a True AI Agent? Rethinking the Pursuit of AutonomyCassie Kozyrkov on DataFramedTIOBE Index for November 2024Community discussion on FortranTutorial: High Performance Data Manipulation in Python: pandas 2.0 vs. polarsNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here.What makes a database modern, and why does it matter? In a world where we face countless choices, how do you build systems that not only scale but also make life easier for your teams? And with AI reshaping industries and workflows, how do businesses bridge the gap between legacy systems and cutting-edge applications?Sahir Azam is the Chief Product Officer at MongoDB. He has been with MongoDB since 2016, where he launched the industry’s first developer data platform, MongoDB Atlas, and scaled the company’s thriving cloud business from the ground up. He also serves on the boards of Temporal and Observe, Inc, a cloud data observability startup. Sahir joined MongoDB from Sumo Logic, where he managed platform, pricing, packaging, and technology partnerships. Before Sumo Logic, he launched VMware's first organically developed SaaS management product and grew their management tools business to $1B+ in revenue. Earlier in his career, Sahir also held technical and sales-focused roles at DynamicOps, BMC Software, and BladeLogic.In the episode, Richie and Sahir Azam explore the evolution of databases beyond NoSQL, enhancing developer productivity, integrating AI capabilities, modernizing legacy systems, and much more.Links Mentioned in the Show:MongoDBConnect with SahirCourse: Introduction to MongoDB in PythonRelated Episode: Not Only Vector Databases: Putting Databases at the Heart of AI, with Andi Gutmans, VP and GM of Databases at GoogleRewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here.Edge computing is poised to transform industries by bringing computation and data storage closer to the source of data generation. This shift unlocks new types of value creation with data & AI and allows for a privacy-first and deeply personalized use of AI on our devices. What will the edge computing transition look like? How do you ensure applications are edge-ready, and what is the role of AI in the transition? Derek Collison is the founder and CEO at Synadia. He is an industry veteran, entrepreneur and pioneer in large-scale distributed systems and cloud computing. Derek founded Synadia Communications and Apcera, and has held executive positions at Google, VMware, and TIBCO Software. He is also an active angel investor and a technology futurist around Artificial Intelligence, Machine Learning, IOT and Cloud Computing.Justyna Bak is VP of Marketing at Synadia. Justyna is a versatile executive bridging Marketing, Sales and Product, a spark-plug for innovation at startups and Fortune 100 and a tech expert in Data Analytics and AI, AppDev and Networking. She is an astute influencer, panelist and presenter (Google, HBR) and a respected leader in Silicon Valley and Europe.In the episode, Richie, Derek, and Justyna explore the transition from cloud to edge computing, the benefits of reduced latency, real-time decision-making in industries like manufacturing and retail, the role of AI at the edge, and the future of edge-native applications, and much more.Links Mentioned in the Show:SynadiaConnect with Derek and JustynaCourse: Understanding Cloud ComputingRelated Episode: The Database is the Operating System with Mike Stonebraker, CTO & Co-Founder At DBOSRewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here.With the EU AI Act coming into effect, the AI industry faces a pivotal moment. This regulation is a landmark step for AI governance and challenges data and AI teams to rethink their approach to AI development and deployment. How will this legislation influence the way AI systems are built and used? What are the key compliance requirements that organizations need to be aware of? And how can companies balance regulatory obligations with the drive for innovation and growth?Dan Nechita led the technical negotiations for the EU Artificial Intelligence Act on behalf of the European Parliament. For the 2019-2024 mandate, besides artificial intelligence, he focused on digital regulation, security and defense, and the transatlantic partnership as Head of Cabinet for Dragos Tudorache, MEP. Previously, he was a State Counselor for the Romanian Prime Minister with a mandate on e-governance, digitalization, and cybersecurity. He worked at the World Security Institute (the Global Zero nuclear disarmament initiative); at the Brookings Institution Center of Executive Education; as a graduate teaching assistant at the George Washington University; at the ABC News Political Unit; and as a research assistant at the Arnold A. Saltzman Institute of War and Peace at Columbia. He is an expert project evaluator for the European Commission and a member of expert AI working groups with the World Economic Forum and the United Nations. Dan is a graduate of the George Washington University (M.A.) and Columbia University in the City of New York (B.A.).In the episode, Adel and Dan explore the EU AI Act's significance, risk classification frameworks, organizational compliance strategies, the intersection with existing regulations, AI literacy requirements, and the future of AI legislation, and much more.Links Mentioned in the Show:The EU AI ActConnect with DanCourse: Understanding the EU AI ActRelated Episode: Guardrails for the Future of AI with Viktor Mayer-Schönberger, Professor of Internet Governance and Regulation at the University of OxfordRewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here.The convergence of AI and business intelligence is creating new opportunities for innovation. As AI becomes more embedded in BI tools, the challenge lies in fostering a data-driven culture within organizations. How can professionals bridge the gap between intuition and data-driven decision-making? What strategies can be employed to cultivate a culture where data is at the forefront of business decisions? And how can AI tools be leveraged to make data insights more accessible to all employees?Omri Kohl is the CEO and co-founder of Pyramid Analytics, the Trusted Analytics Platform built for the enterprise. He leads Pyramid’s strategy and operations through a fast-growing data and analytics market. Kohl brings a deep understanding of analytics and AI technologies, valuable management experience, and a natural ability to challenge conventional thinking. Since Kohl founded Pyramid in 2009, it has achieved significant market success and customer growth. Kohl is a highly experienced entrepreneur with a proven track record developing and managing fast-growth companies.In the episode, Richie and Omri explore the evolution of BI with AI, the importance of data-driven culture, the role of generative BI in democratizing insights, the balance between intuition and data, and much more.Links Mentioned in the Show:Pyramid AnalyticsConnect with OmriPyramid Analytics GenBI DemoCourse: Introduction to Data CultureRelated Episode: Self-Service Business Intelligence with Sameer Al-Sakran, CEO at MetabaseRewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
Welcome to DataFramed Industry Roundups! In this series of episodes, Adel & Richie sit down to discuss the latest and greatest in data & AI. In this episode, we touch upon the brewing rivalry between OpenAI and Anthropic, discuss Claude's new computer use feature, Google's NotebookLM and how its implications for the UX/UI of AI products, and a lot more.Links mentioned in the show:Chatbot Arena LeaderboardNotebookLMAnthropic Computer UseIntroducing OpenAI o1-previewNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here.Integrating generative AI with robust databases is becoming essential. As organizations face a plethora of database options and AI tools, making informed decisions is crucial for enhancing customer experiences and operational efficiency. How do you ensure your AI systems are powered by high-quality data? And how can these choices impact your organization's success?Gerrit Kazmaier is the VP and GM of Data Analytics at Google Cloud. Gerrit leads the development and design of Google Cloud’s data technology, which includes data warehousing and analytics. Gerrit’s mission is to build a unified data platform for all types of data processing as the foundation for the digital enterprise. Before joining Google, Gerrit served as President of the HANA & Analytics team at SAP in Germany and led the global Product, Solution & Engineering teams for Databases, Data Warehousing and Analytics. In 2015, Gerrit served as the Vice President of SAP Analytics Cloud in Vancouver, Canada.In this episode, Richie and Gerrit explore the transformative role of AI in data tools, the evolution of dashboards, the integration of AI with existing workflows, the challenges and opportunities in SQL code generation, the importance of a unified data platform, leveraging unstructured data, and much more.Links Mentioned in the Show:Google CloudConnect with GerritThinking Fast and Slow by Daniel KahnemanCourse: Introduction to GCPRelated Episode: Not Only Vector Databases: Putting Databases at the Heart of AI, with Andi Gutmans, VP and GM of Databases at GoogleRewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here.We’re often caught chasing the dream of “self-serve” data—a place where data empowers stakeholders to answer their questions without a data expert at every turn. But what does it take to reach that point? How do you shape tools that empower teams to explore and act on data without the usual bottlenecks? And with the growing presence of natural language tools and AI, is true self-service within reach, or is there still more to the journey?Sameer Al-Sakran is the CEO at Metabase, a low-code self-service analytics company. Sameer has a background in both data science and data engineering so he's got a practitioner's perspective as well as executive insight. Previously, he was CTO at Expa and Blackjet, and the founder of SimpleHadoop and Adopilot.In the episode, Richie and Sameer explore self-serve analytics, the evolution of data tools, GenAI vs AI agents, semantic layers, the challenges of implementing self-serve analytics, the problem with data-driven culture, encouraging efficiency in data teams, the parallels between UX and data projects, exciting trends in analytics, and much more. Links Mentioned in the Show:MetabaseConnect with SameerArticles from Metabase on jargon, information budgets, analytics mistakes, and data model mistakesCourse: Introduction to Data CultureRelated Episode: Towards Self-Service Data Engineering with Taylor Brown, Co-Founder and COO at FivetranRewatch Sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here.Data is no longer just for coders. With the rise of low-code tools, more people across organizations can access data insights without needing programming skills. But how can companies leverage these tools effectively? And what steps should they take to integrate them into existing workflows while upskilling their teams? Michael Berthold is CEO and co-founder at KNIME, an open source data analytics company. He has more than 25 years of experience in data science, working in academia, most recently as a full professor at Konstanz University (Germany) and previously at University of California (Berkeley) and Carnegie Mellon, and in industry at Intel’s Neural Network Group, Utopy, and Tripos. Michael has published extensively on data analytics, machine learning, and artificial intelligence.In the episode, Adel and Michael explore low-code data science, the adoption of low-code data tools, the evolution of data science workflows, upskilling, low-code and code collaboration, data literacy, integration with AI and GenAI tools, the future of low-code data tools and much more. Links Mentioned in the Show:KNIMEConnect with MichaelCode Along: Low-Code Data Science and Analytics with KNIMECourse: Introduction to KNIMERelated Episode: No-Code LLMs In Practice with Birago Jones & Karthik Dinakar, CEO & CTO at PiensoNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here.Staying ahead means knowing what’s happening right now—not minutes or hours later. Real-time analytics promises to help teams react faster, make informed choices, and even predict issues before they arise. But implementing these systems is no small feat, and it requires careful alignment between technical capabilities and business needs. How do you ensure that real-time data actually drives impact? And what should organizations consider to make sure their real-time analytics investments lead to tangible benefits?Zuzanna Stamirowska is the CEO of Pathway.com - the fastest data processing engine on the market which makes real-time intelligence possible. Zuzanna is also the author of the state-of-the-art forecasting model for maritime trade published by the National Academy of Sciences of the USA. While working on this project she saw that the digitization of traditional industries was slowed down by the lack of a software infrastructure capable of doing automated reasoning on top of data streams, in real time. This was the spark to launch Pathway. She holds a Master’s degree in Economics and Public Policy from Sciences Po, Ecole Polytechnique, and ENSAE, as well as a PhD in Complexity Science..Hélène Stanway is Independent Advisor & Consultant at HMLS Consulting Ltd. Hélène is an award-winning and highly effective insurance leader with a proven track record in emerging technologies, innovation, operations, data, change, and digital transformation. Her passion for actively combining the human element, design, and innovation alongside technology has enabled companies in the global insurance market to embrace change by achieving their desired strategic goals, improving processes, increasing efficiency, and deploying relevant tools. With a special passion for IoT and Sensor Technology, Hélène is a perpetual learner, driven to help delegates succeed. In the episode, Richie, Zuzanna and Hélène explore real-time analytics, their operational impact, use-cases of real-time analytics across industries, the benefits of adopting real-time analytics, the key roles and stakeholders you need to make that happen, operational challenges, strategies for effective adoption, the real-time of the future, common pitfalls, and much more. Links Mentioned in the Show:PathwayConnect with Zuzanna and HélèneLiArticle: What are digital twins and why do we need them?Course: Time Series Analysis in Power BIRelated Episode: How Real Time Data Accelerates Business Outcomes with George TrujilloSign up to RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data
We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here.Understanding where the data you use comes from, how to use it responsibly, and how to maximize its value has become essential. But as data sources multiply, so do the complexities around data privacy, customization, and ownership. How can companies capture and leverage the right data to create meaningful customer experiences while respecting privacy? And as data drives more personalized interactions, what steps can businesses take to protect sensitive information and navigate the increasingly complex regulatory picture? Jonathan Bloch is CEO at Exchange Data International (EDI) and a seasoned businessman with 40 years experience in information provision. He started work in the newsletter industry and ran the US subsidiary of a UK public company before joining its main board as head of its publishing division. He has been a director and/or chair of several companies and is currently a non executive director of an FCA registered investment bank. In 1994 he founded Exchange Data International (EDI) a London based financial data provider. EDI now has over 450 clients across three continents and is based in the UK, USA, India and Morocco employing 500 people.Scott Voigt is CEO and co-founder at Fullstory. Scott has enjoyed helping early-stage software businesses grow since the mid 90s, when he helped launch and take public nFront—one of the world's first Internet banking service providers. Prior to co-founding Fullstory, Voigt led marketing at Silverpop before the company was acquired by IBM. Previously, he worked at Noro-Moseley Partners, the Southeast's largest Venture firm, and also served as COO at Innuvo, which was acquired by Google. Scott teamed up with two former Innuvo colleagues, and the group developed the earliest iterations of Fullstory to understand how an existing product was performing. It was quickly apparent that this new platform provided the greatest value—and the rest is history.In the episode, Richie, Jonathan and Scott explore first-party vs third-party data, protecting corporate data, behavioral data, personalization, data sourcing strategies, platforms for storage and sourcing, data privacy, synthetic data, regulations and compliance, the future of data collection and storage, and much more. Links Mentioned in the Show:FullstoryExchange Data InternationalConnect with Jonathan and ScottCourse: Understanding GDPRRelated Episode: How Data and AI are Changing Data Management with Jamie Lerner, CEO, President, and Chairman at QuantumSign up to RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile...
Machine learning and AI have become essential tools for delivering real-time solutions across industries. However, as these technologies scale, they bring their own set of challenges—complexity, data drift, latency, and the constant fight between innovation and reliability. How can we deploy models that not only enhance user experiences but also keep up with changing demands? And what does it take to ensure that these solutions are built to adapt, perform, and deliver value at scale?Rachita Naik is a Machine Learning (ML) Engineer at Lyft, Inc., and a recent graduate of Columbia University in New York. With two years of professional experience, Rachita is dedicated to creating impactful software solutions that leverage the power of Artificial Intelligence (AI) to solve real-world problems. At Lyft, Rachita focuses on developing and deploying robust ML models to enhance the ride-hailing industry’s pickup time reliability. She thrives on the challenge of addressing ML use cases at scale in dynamic environments, which has provided her with a deep understanding of practical challenges and the expertise to overcome them. Throughout her academic and professional journey, Rachita has honed a diverse skill set in AI and software engineering and remains eager to learn about new technologies and techniques to improve the quality and effectiveness of her work. In the episode, Adel and Rachita explore how machine learning is leveraged at Lyft, the primary use-cases of ML in ride-sharing, what goes into an ETA prediction pipeline, the challenges of building large scale ML systems, reinforcement learning for dynamic pricing, key skills for machine learning engineers, future trends across machine learning and generative AI and much more. Links Mentioned in the Show:Engineering at Lyft on MediumConnect with RachitaResearch Paper—A Better Match for Drivers and Riders: Reinforcement Learning at LyftCareer Track: Machine Learning EngineerRelated Episode: Why ML Projects Fail, and How to Ensure Success with Eric Siegel, Founder of Machine Learning Week, Former Columbia Professor, and Bestselling AuthorSign up to RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
As AI continually changes how businesses operate, new questions emerge around ethics and privacy. Nowadays, algorithms can set prices and personalize offers, but how do companies ensure they’re doing this responsibly? What does it mean to be transparent with customers about data use, and how can businesses avoid unintended bias? Balancing innovation with trust is key, but achieving this balance isn’t always straightforward.Dr. Jose Mendoza is Academic Director and Clinical Associate Professor in Integrated Marketing at NYU, and was formerly an Associate Professor of Practice at The University of Arizona in Tucson, Arizona. His focus is on consumer pricing, digital retailing, intelligent retail stores, neuromarketing, big data, artificial intelligence, and machine learning. Previously, he taught marketing courses at Sacred Heart University and Western Michigan University. He is also an experienced senior global marketing executive with over 18 years of experience in global marketing alone and a career as an Engineer in Information Sciences. Dr. Mendoza is also a Doctoral Researcher in Strategic and Global pricing, Consumer Behavior, and Pricing Research methodologies. He had international roles in Latin America, Europe, and the USA with scope in over 50 countries. In the episode, Richie and Jose explore AI-driven pricing, consumer perceptions and ethical pricing, the complexity of dynamic pricing models, explainable AI, data privacy and customer trust, legal and ethical guardrails, innovations in dynamic pricing and much more. Links Mentioned in the Show:NYUConnect with JoseAmazon Dynamic Pricing Strategy in 2024Course: AI EthicsRelated Episode: The Future of Marketing Analytics with Cory Munchbach, CEO at BlueConicSign up to RADAR: Forward EditionNew 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 recent rapid advancements in AI comes the challenge of navigating an ever-changing field of play, while ensuring the tech we use serves real-world needs. As AI becomes more ingrained in business and everyday life, how do we balance cutting-edge development with practicality and ethical responsibility? What steps are necessary to ensure AI’s growth benefits society, aligns with human values, and avoids potential risks? What similarities can we draw between the way we think, and the way AI thinks for us?Terry Sejnowski is one of the most influential figures in computational neuroscience. At the Salk Institute for Biological Studies, he runs the Computational Neurobiology Laboratory, and hold the Francis Crick Chair. At the University of California, San Diego, he is a Distinguished Professor and runs a neurobiology lab. Terry is also the President of the Neural Information Processing (NIPS) Foundation, and an organizer of the NeurIPS AI conference. Alongside Geoff Hinton, Terry co-invented the Boltzmann machine technique for machine learning. He is the author of over 500 journal articles on neuroscience and AI, and the book "ChatGPT and the Future of AI".In the episode, Richie and Terry explore the current state of AI, historical developments in AI, the NeurIPS conference, collaboration between AI and neuroscience, AI’s shift from academia to industry, large vs small LLMs, creativity in AI, AI ethics, autonomous AI, AI agents, superintelligence, and much more. Links Mentioned in the Show:NeurIPS ConferenceTerry’s Book—ChatGPT and the Future of AI: The Deep Language RevolutionConnect with TerryTerry on SubstackCourse: Data Communication ConceptsRelated Episode: Guardrails for the Future of AI with Viktor Mayer-Schönberger, Professor of Internet Governance and Regulation at the University of OxfordSign up to RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
Generative AI and data are more interconnected than ever. If you want quality in your AI product, you need to be connected to a database with high quality data. But with so many database options and new AI tools emerging, how do you ensure you’re making the right choices for your organization? Whether it’s enhancing customer experiences or improving operational efficiency, understanding the role of your databases in powering AI is crucial. Andi Gutmans is the General Manager and Vice President for Databases at Google. Andi’s focus is on building, managing, and scaling the most innovative database services to deliver the industry’s leading data platform for businesses. Prior to joining Google, Andi was VP Analytics at AWS running services such as Amazon Redshift. Prior to his tenure at AWS, Andi served as CEO and co-founder of Zend Technologies, the commercial backer of open-source PHP. Andi has over 20 years of experience as an open source contributor and leader. He co-authored open source PHP. He is an emeritus member of the Apache Software Foundation and served on the Eclipse Foundation’s board of directors. He holds a bachelor’s degree in computer science from the Technion, Israel Institute of Technology.In the episode, Richie and Andi explore databases and their relationship with AI and GenAI, key features needed in databases for AI, GCP database services, AlloyDB, federated queries in Google Cloud, vector databases, graph databases, practical use cases of AI in databases and much more. Links Mentioned in the Show:GCPConnect with AndiAlloyDB for PostgreSQLCourse: Responsible AI Data ManagementRelated Episode: The Power of Vector Databases and Semantic Search with Elan Dekel, VP of Product at PineconeSign up to RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
Mastering the technical side of data and AI is one thing, but communicating those insights effectively is a whole different challenge. How do you make sure your data is understood, acted upon, and influences decisions? It’s not just about presenting the right numbers—it’s about framing them in a way that resonates with different audiences. But how do you tailor your communication to different stakeholders and ensure your message cuts through? What strategies can you use to make your insights truly impactful?Wes Kao is an entrepreneur, marketer, coach, and advisor who writes at newsletter.weskao.com. She is co-founder of Maven, an edtech company that raised $25M from First Round and Andreessen Horowitz. Previously, she co-founded the altMBA with bestselling author Seth Godin.In the episode, Richie and Wes explore communication skills, tailoring to your audience, persuasion vs information, feedback and behavioral change, intellectual honesty, judgement and analytical thinking, management and ownership, dealing with mistakes, conflict management, career advice for data practitioners and much more. Links Mentioned in the Show:Wes’ WebsiteConnect with Wes10,000 Hours Concept by Malcolm GladwellCourse: Data Communication ConceptsRelated Episode: Making Better Decisions using Data & AI with Cassie Kozyrkov, Google's First Chief Decision ScientistSign up to RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
Building a robust data infrastructure is crucial for any organization looking to leverage AI and data-driven insights. But as your data ecosystem grows, so do the challenges of managing, securing, and scaling it. How do you ensure that your data infrastructure not only meets today’s needs but is also prepared for the rapid changes in technology tomorrow? What strategies can you adopt to keep your organization agile, while ensuring that your data investments continue to deliver value and support business goals?Saad Siddiqui is a venture capitalist for Titanium Ventures. Titanium focus on enterprise technology investments, particularly focusing on next generation enterprise infrastructure and applications. In his career, Saad has deployed over $100M in venture capital in over a dozen companies. In previous roles as a corporate development executive, he has executed M&A transactions valued at over $7 billion in aggregate. Prior to Titanium Ventures he was in corporate development at Informatica and was a member of Cisco's venture investing and acquisitions team covering cloud, big data and virtualization. In the episode, Richie and Saad explore the business impacts of data infrastructure, getting started with data infrastructure, the roles and teams you need to get started, scalability and future-proofing, implementation challenges, continuous education and flexibility, automation and modernization, trends in data infrastructure, and much more. Links Mentioned in the Show:Titanium VenturesConnect with SaadCourse - Artificial Intelligence (AI) StrategyRelated Episode: How are Businesses Really Using AI? With Tathagat Varma, Global TechOps Leader at Walmart Global TechRewatch sessions from RADAR: AI EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
Businesses are collecting more data than ever before. But is bigger always better? Many companies are starting to question whether massive datasets and complex infrastructure are truly delivering results or just adding unnecessary costs and complications. How can you make sure your data strategy is aligned with your actual needs? What if focusing on smaller, more manageable datasets could improve your efficiency and save resources, all while delivering the same insights?Ryan Boyd is the Co-Founder & VP, Marketing + DevRel at MotherDuck. Ryan started his career as a software engineer, but since has led DevRel teams for 15+ years at Google, Databricks and Neo4j, where he developed and executed numerous marketing and DevRel programs. Prior to MotherDuck, Ryan worked at Databricks and focussed the team on building an online community during the pandemic, helping to organize the content and experience for an online Data + AI Summit, establishing a regular cadence of video and blog content, launching the Databricks Beacons ambassador program, improving the time to an “aha” moment in the online trial and launching a University Alliance program to help professors teach the latest in data science, machine learning and data engineering.In the episode, Richie and Ryan explore data growth and computation, the data 1%, the small data movement, data storage and usage, the shift to local and hybrid computing, modern data tools, the challenges of big data, transactional vs analytical databases, SQL language enhancements, simple and ergonomic data solutions and much more. Links Mentioned in the Show:MotherDuckThe Small Data ManifestoConnect with RyanSmall DataSF conferenceRelated Episode: Effective Data Engineering with Liya Aizenberg, Director of Data Engineering at AwayRewatch sessions from RADAR: AI EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
Businesses are constantly racing to stay ahead by adopting the latest data tools and AI technologies. But with so many options and buzzwords, it’s easy to get lost in the excitement without knowing whether these tools truly serve your business. How can you ensure that your data stack is not only modern but sustainable and agile enough to adapt to changing needs? What does it take to build data products that deliver real value to your teams while driving innovation?Adrian Estala is VP, Field Chief Data Officer and the host of Starburst TV. With a background in leading Digital and IT Portfolio Transformations, he understands the value of creating executive frameworks that focus on material business outcomes. Skilled with getting the most out of data-driven investments, Adrian is your trusted adviser to navigating complex data environments and integrating a Data Mesh strategy in your organization. In the episode, Richie and Adrian explore the modern data stack, agility in data, collaboration between business and data teams, data products and differing ways of building them, data discovery and metadata, data quality, career skills for data practitioners and much more. Links Mentioned in the Show:StarburstConnect with AdrianCareer Track: Data Engineer in PythonRelated Episode: How this Accenture CDO is Navigating the AI RevolutionRewatch sessions from RADAR: AI EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
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mrs rime

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Jan 16th
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Sajjad Dehqani

can you list the tools for monitoring and so on ?

Nov 15th
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Jorge Arbelaez

interesting interview

May 23rd
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Anh D Tran

excuse me im just taking note here: some process with the truck guy tips how to do data science in big org with google guy from superdatascience eda explaratory analysys from tukey

May 22nd
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Moncsi

Hi there, is it possible to get links to the data philanthropy organisations? I'm super curious. Thank you!

Mar 25th
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Jokus Jodokus

The short section about the connection between data scientists and project managers resonated with me

Feb 26th
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gg

400 million people do not have diabetic retinopathy, incorrect statistic.

Jan 23rd
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Paolo Eusebi

Amazing episode! How many listeners worked with Stan in R? What are their impressions over other bayesian software?

Oct 9th
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Rafael Anjos

The contents are very good. Thank you for your good job

Sep 18th
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Anthony Giancursio

Ol

Jul 19th
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Alessandro Surace

Hi Hugo thanks for this podcast. Would be great to have the relevant urls, as the shownotes and others, in the podcast description.

Jun 20th
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