The promise of AI in enterprise settings is enormous, but so are the privacy and security challenges. How do you harness AI's capabilities while keeping sensitive data protected within your organization's boundaries? Private AI—using your own models, data, and infrastructure—offers a solution, but implementation isn't straightforward. What governance frameworks need to be in place? How do you evaluate non-deterministic AI systems? When should you build in-house versus leveraging cloud services? As data and software teams evolve in this new landscape, understanding the technical requirements and workflow changes is essential for organizations looking to maintain control over their AI destiny. Manasi Vartak is Chief AI Architect and VP of Product Management (AI Platform) at Cloudera. She is a product and AI leader with more than a decade of experience at the intersection of AI infrastructure, enterprise software, and go-to-market strategy. At Cloudera, she leads product and engineering teams building low-code and high-code generative AI platforms, driving the company’s enterprise AI strategy and enabling trusted AI adoption across global organizations. Before joining Cloudera through its acquisition of Verta, Manasi was the founder and CEO of Verta, where she transformed her MIT research into enterprise-ready ML infrastructure. She scaled the company to multi-million ARR, serving Fortune 500 clients in finance, insurance, and capital markets, and led the launch of enterprise MLOps and GenAI products used in mission-critical workloads. Manasi earned her PhD in Computer Science from MIT, where she pioneered model management systems such as ModelDB — foundational work that influenced the development of tools like MLflow. Earlier in her career, she held research and engineering roles at Twitter, Facebook, Google, and Microsoft. In the episode, Richie and Manasi explore AI's role in financial services, the challenges of AI adoption in enterprises, the importance of data governance, the evolving skills needed for AI development, the future of AI agents, and much more. Links Mentioned in the Show: ClouderaCloudera Evolve ConferenceCloudera Agent StudioConnect with ManasiCourse: Introduction to AI AgentsRelated Episode: RAG 2.0 and The New Era of RAG Agents with Douwe Kiela, CEO at Contextual AI & Adjunct Professor at Stanford UniversityRewatch RADAR AI  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

The relationship between humans and AI in the workplace is rapidly evolving beyond simple automation. As companies deploy thousands of AI agents to handle everything from expense approvals to customer success management, a new paradigm is emerging—one where humans become orchestrators rather than operators. But how do you determine which processes should be handled by AI and which require human judgment? What governance structures need to be in place before deploying AI at scale? With the potential to automate up to 80% of business processes, organizations must carefully consider not just the technology, but the human element of AI-driven transformation. Steve Lucas is the Chairman and CEO of Boomi, marking his third tenure as CEO. With nearly 30 years of enterprise software leadership, he has held senior roles at leading cloud organizations including Marketo, iCIMS, Adobe, SAP, Salesforce, and BusinessObjects. He led Marketo through its multi-billion-dollar acquisition by Adobe and drove strategic growth at iCIMS, delivering significant investments and transformation. A proven leader in scaling software companies, Steve is also the author of the national bestseller Digital Impact and holds a business degree from the University of Colorado. In the episode, Richie and Steve explore the importance of choosing the right tech stack for your business, the challenges of managing complex systems, the role of AI in transforming business processes, and the need for effective AI governance. They also discuss the future of AI-driven enterprises and much more. Links Mentioned in the Show: BoomiSteve’s Book - Digital Impact: The Human Element of AI-Driven TransformationWhat is the OSI Model?Connect with SteveSkill Track: AI Business FundamentalsRelated Episode: New Models for Digital Transformation with Alison McCauley Chief Advocacy Officer at Think with AI & Founder of Unblocked FutureRewatch RADAR AI  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

The role of data and AI engineers is more critical than ever. With organizations collecting massive amounts of data, the challenge lies in building efficient data infrastructures that can support AI systems and deliver actionable insights. But what does it take to become a successful data or AI engineer? How do you navigate the complex landscape of data tools and technologies? And what are the key skills and strategies needed to excel in this field?  Deepak Goyal is a globally recognized authority in Cloud Data Engineering and AI. As the Founder & CEO of Azurelib Academy, he has built a trusted platform for advanced cloud education, empowering over 100,000 professionals and influencing data strategies across Fortune 500 companies. With over 17 years of leadership experience, Deepak has been at the forefront of designing and implementing scalable, real-world data solutions using cutting-edge technologies like Microsoft Azure, Databricks, and Generative AI. In the episode, Richie and Deepak explore the fundamentals of data engineering, the critical skills needed, the intersection with AI roles, career paths, and essential soft skills. They also discuss the hiring process, interview tips, and the importance of continuous learning in a rapidly evolving field, and much more. Links Mentioned in the Show: AzureLibAzureLib Academy Connect with DeepakGet Certified! Azure FundamentalsRelated Episode: Effective Data Engineering with Liya Aizenberg, Director of Data Engineering at AwaySign up to attend RADAR: Skills 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

AI features and products are the hottest area of software development. Creating high quality AI software is both essential and challenging for many businesses. In this episode, we look at retrieval augmented generation, an important technique for improving text generation quality in AI applications. Beyond technical measures, we look at the broader quality problem for AI applications. How do you ensure your AI applications are effective and secure? What steps should you take to integrate AI into your existing data governance frameworks? And how do you measure the success of these AI-driven solutions? Theresa Parker is the Director of Product Management at Rocket Software. She has 25 years of experience as a technology executive with a focus on software development processes, consultancy, and business development. Her recent work in content management focuses on the use of AI and RAG to improve content discoverability. Sudhi Balan is the Chief Technology Officer for AI & Cloud. He leads the AI and data teams for data modernization, driving AI adoption of Rocket's structured and unstructured data products. He also shapes AI strategy for Rocket’s infrastructure and app portfolio. He has earned patents for safe and scalable applications of transformational technology. Previously, he led digital transformation and hybrid cloud strategy for Rocket’s unstructured data business and was Senior Director of Product Development at ASG. In the episode, Richie, Theresa, and Sudhi explore retrieval-augmented generation, its applications in customer support and loan processing, the importance of data governance and privacy, the role of testing and guardrails in AI, cost management strategies, and the potential of AI to transform customer experiences, and much more. Links Mentioned in the Show: Rocket SoftwareConnect with Theresa and SudhiCourse: Retrieval Augmented Generation (RAG) with LangChainRelated Episode: Getting Generative AI Into Production with Lin Qiao, CEO and Co-Founder of Fireworks AIRewatch sessions from RADAR: Forward 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

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 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

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 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

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 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

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 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

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 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

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 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

In today's fast-paced digital world, managing IT operations is more complex than ever. With the rise of cloud services, microservices, and constant software deployments, the pressure on IT teams to keep everything running smoothly is immense. But how do you keep up with the ever-growing flood of data and ensure your systems are always available? AIOps is the use of artificial intelligence to automate and scale IT operations. But what exactly is AIOps, and how can it transform your IT operations? Assaf Resnick is the CEO and Co-Founder of BigPanda. Before founding BigPanda, Assaf was an investor at Sequoia Capital, where he focused on early and growth-stage investing in software, internet, and mobile sectors. Assaf’s time at Sequoia gave him a front-row seat to the challenges of IT scale, complexity, and velocity faced by Operations teams in rapidly scaling and accelerating organizations. This is the problem that Assaf founded BigPanda to solve. In the episode, Richie and Assaf explore AIOps, how AIOps helps manage increasingly complex IT operations, how AIOps differs from DevOps and MLOps, examples of AIOps projects, a real world application of AIOps, the key benefits of AIOps, how to implement AIOps, excitement in the space, how GenAI is improving AIOps and much more.  Links Mentioned in the Show: BigPandaGartner: Market Guide for AIOps Platforms[Course] Implementing AI Solutions in BusinessRelated Episode: Adding AI to the Data Warehouse with Sridhar Ramaswamy, CEO at SnowflakeSign up to RADAR: AI Edition 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

With seemingly every organization wanting to enhance their AI capabilities, questions arise about who should be in charge of these initiatives. At the moment, it’s likely a CTO, CIO, or CDO, or a mixture of the three. The gold standard is to have someone in the C-suite whose sole focus is their AI projects: the Chief AI Officer. This role is so new that it's not yet widely understood. In this episode, we explore what the CAIO job entails. Philipp Herzig is the Chief AI Officer at SAP. He’s held a variety of roles within SAP, most recently SVP Head of Cross Product Engineering & Experience, however his experience covers intelligent enterprise & cross-architecture, head of engineering for cloud-native apps, a software development manager, and product owner.  In the full episode, Richie and Philipp explore what his day-to-day responsibilities are as a CAIO, the holistic approach to cross-team collaboration, non-technical interdepartmental work, AI strategy and implementation, challenges and success metrics, how to approach high-value AI use cases, insights into current AI developments and the importance of continuous learning, the exciting future of AI and much more. 

Links Mentioned in the Show: SAP’s AI CoPilot JouleSAP[Course] Implementing AI Solutions in BusinessRelated Episode: How Walmart Leverages Data & AI with Swati Kirti, Sr Director of Data Science at WalmartRewatch sessions from 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

Snowflake has been foundational in the data space for years. In the mid-2010s, the platform was a major driver of moving data to the cloud. More recently, it's become apparent that combining data and AI in the cloud is key to accelerating innovation. Snowflake has been rapidly adding AI features to provide value to the modern data stack, but what’s really been going on under the hood? At the time of recording, Sridhar Ramaswamy was the SVP of AI at Snowflake, being appointed CEO at Snowflake in February 2024. Sridhar was formerly Co-Founder of Neeva, acquired in 2023 by Snowflake. Before founding Neeva, Ramaswamy oversaw Google's advertising products, including search, display, video advertising, analytics, shopping, payments, and travel. He joined Google in 2003 and was part of the growth of AdWords and Google's overall advertising business. He spent more than 15 years at Google, where he started as a software engineer and rose to SVP of Ads & Commerce.  In the episode, Richie and Sridhar explore Snowflake and its uses, how generative AI is changing the attitudes of leaders towards data, how NLP and AI have impacted enterprise business operations as well as new applications of AI in an enterprise environment, the challenges of enterprise search, the importance of data quality, management and the role of semantic layers in the effective use of AI, a look into Snowflakes products including Snowpilot and Cortex, the collaboration required for successful data and AI projects, advice for organizations looking to improve their data management 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: SnowflakeSnowflake acquires Neeva to accelerate search in the Data Cloud through generative AIUse AI in Seconds with Snowflake Cortex[Course] Introduction to SnowflakeRelated Episode: Why AI will Change Everything—with Former Snowflake CEO, Bob MugliaSign up to a...

As companies scale and become more successful, new horizons open, but with them come unexpected challenges. The influx of revenue and expansion of operations often reveal hidden complexities that can hinder efficiency and inflate costs. In this tricky situation, data teams can find themselves entangled in a web of obstacles that slow down their ability to innovate and respond to ever-changing business needs. Enter cloud analytics—a transformative solution that promises to break down barriers and unleash potential. By migrating analytics to the cloud, organizations can navigate the growing pains of success, cutting costs, enhancing flexibility, and empowering data teams to work with agility and precision. John Knieriemen is the Regional Business Lead for North America at Exasol, the market-leading high-performance analytics database. Prior to joining Exasol, he served as Vice President and General Manager at Teradata during an 11-year tenure with the company. John is responsible for strategically scaling Exasol’s North America business presence across industries and expanding the organization’s partner network.  Solongo Erdenekhuyag is the former Customer Success and Data Strategy Leader at Exasol. Solongo is skilled in strategy, business development, program management, leadership, strategic partnerships, and management. In the episode, Richie, Solongo, and John cover the motivation for moving analytics to the cloud, economic triggers for migration, success stories from organizations who have migrated to the cloud, the challenges and potential roadblocks in migration, the importance of flexibility and open-mindedness and much more.  Links from the Show ExasolAmazon S3Azure Blob StorageGoogle Cloud StorageBigQueryAmazon RedshiftSnowflake[Course] Understanding Cloud Computing[Course] AWS Cloud Concepts