Podcast
Data Architecture Elevator
Hosted by Agile Lab s.r.l. · EN
Welcome to Data Architecture Elevator, a vibrant podcast produced by Agile Lab (www.agilelab.it). Join our expert architects for an engaging hour of friendly chat as they explore the hottest topics in the data architecture space. Each episode dives into innovative solutions, industry trends, and practical insights to elevate your understanding of data architecture. Whether you’re a seasoned pro or just curious, hop on and ride the elevator with us to new heights in data innovation!
10episodes
Episodes
Newest firstAll episodes
Advanced LLM Optimization techniques
Apr 7, 202500:15:54Tap to summarizeWelcome to another Data Architecture Elevator podcast! Today's discussion is hosted by Paolo Platter supported by our experts Antonino Ingargiola and Irene Donato. In this episode, we explore effective strategies for optimizing large language models (LLMs) for inference tasks with multimodal data like audio, text, images, and video. We discuss the shift from online APIs to hosted models, choosing smaller, task-specific models, and leveraging fine-tuning, distillation, quantization, and tensor fusion techniques. We also highlight the role of specialized inference servers such as Triton and Dynamo, and how Kubernetes helps manage horizontal scaling. Don't forget to follow us on LinkedIn! Enjoy!
Transcribe →Agentic AI, Model Context Protocol and Data Products
Apr 1, 202500:16:04Tap to summarizeWelcome to another episode of Data Architecture Elevator, hosted by Paolo Platter (https://www.linkedin.com/in/paoloplatter/) and featuring Antonino Ingargiola (https://www.linkedin.com/in/antonino-ingargiola/) and Antonio Murgia (https://www.linkedin.com/in/antonio-murgia/). The conversation explores how Model Context Protocol (MCP), introduced by Anthropic, enables interoperability between LLM-based agentic applications and external systems through a standardized client-server model. In this setup, agents (LLM clients) discover and invoke tools exposed by MCP-compliant servers. This protocol decouples integration logic, allowing systems to interoperate without custom code. The discussion then applies MCP to data products in a data mesh architecture, where output ports (data access), observability ports (data quality and freshness), and control ports (operations) can be exposed as tools via MCP. This allows agents to autonomously query data, evaluate its quality, and even trigger operational commands like restarts or compliance actions. Enjoy it :)
Transcribe →Data Privacy in the Age of Large Language Models
Mar 6, 202500:32:53Tap to summarizeWelcome to another episode of Data Architecture Elevator Podcast! Today we'll tackle another hot topic: Data Privacy related to Large Language Models. Large language models (LLMs) have changed the way we interact with technology, enabling more natural conversations, automating tasks, and generating human-like responses. But as the saying goes, with great power comes great responsibility. The intersection of LLMs and privacy raises crucial questions: How do these models process and store user data? What safeguards exist to prevent unintended data retention? And what steps can businesses take to ensure compliance with data protection regulations? Join the discussion with our host Paolo Platter and our guests Antonio Murgia, Antonino Ingargiola and Irene Donato. Don't forget to follow us on LinkedIn! Enjoy!
Transcribe →Agents vs Tools: Spot the differences!
Mar 3, 202500:16:20Tap to summarizeWelcome to a new episode of Data Architecture Elevator Espresso with an in-depth analysis of agents and tools in the field of Agentic AI. In this episode, hosted by Antonio Murgia and with our dear guest Irene Donato, we'll explore two concepts often used interchangeably but with crucial distinctions. What are the differences between AI Agents and AI Tools? Understanding these differences is vital for businesses and technologists looking to leverage AI effectively. Enjoy!
Transcribe →Espresso - WASM and UDF
Feb 20, 202500:21:58Tap to summarizeHello there! Today we'll explore the usage of WebAssembly to streamline User Defined Functions. We're going to do that with the help of our guest Andrea Fonti and our dear host Antonio Murgia. User-defined functions (UDFs) have long been a powerful tool for extending database and query engine capabilities. From traditional relational databases to modern big data platforms like Hive and Spark, UDFs enable developers to introduce custom logic tailored to their specific needs. However, the existing methods of implementing UDFs often come with significant constraints: rigid language requirements, security concerns, and performance bottlenecks. WebAssembly (Wasm) is a technology that promises a more flexible, secure, and efficient approach to UDF development. Don't forget to follow us on LinkedIn! Enjoy :)
Transcribe →Agentic AI
Feb 12, 202500:40:28Tap to summarizeWe're thrilled to start a new podcast with one of the hottest topic so far: Agentic AI. From autonomous systems to ethical dilemmas, from AI-driven creativity to its impact on business, we dive into this intriguing theme with our host Paolo Platter engaging and interviewing our guests Antonio Murgia (Data Architect) and Antonino Ingargiola (AI Architect) . Enjoy!
Transcribe →Data Privacy and Crypto-Shredding
Dec 17, 202400:58:46Tap to summarizeImagine a world where your sensitive data vanishes—not just deleted, but utterly irretrievable. That’s the magic of crypto-shredding: a technique where encryption keys are destroyed, rendering the data useless, forever. 🔑 Why does this matter? ✅ No keys = No access. ✅ It's clean, efficient, and a data security mic drop. ✅ Essential for GDPR compliance, sensitive records, and peace of mind. In this episode, we break it down: What crypto-shredding is (and isn’t). Real-world use cases and myths busted. When you should consider it for your business. Hosted by Paolo Platter, we will dive into Data Privacy and Crypto-Shredding with the help of Francesco Valentini and Antonio Murgia.
Transcribe →Espresso - Data Science and Data Engineering
Dec 12, 202400:19:14Tap to summarizeHere's a new episode of the Data Architecture Elevator Espresso! Today we'll face the relationship between Data Science and Data Engineering with our own Pietro Peterlongo - https://www.linkedin.com/in/pietro-peterlongo-b7605627/. Pietro is going to provide some insights - with passion and a healthy dose of humor - into different practices and in particular the intersections between Data Scientists and Data Engineers. This episode is hosted by our Antonio Murgia - https://www.linkedin.com/in/antonio-murgia/. Don't forget to follow us on LinkedIn!
Transcribe →Espresso - MLOps
Dec 3, 202400:14:06Tap to summarizeHere's a new episode of the Data Architecture Elevator Espresso, recorded live from our Milan offices! Today we will delve into the topics related to MLOps with Antonino Ingargiola. The Podcast will discuss (from a first-hand perspective) the practices of integrating machine learning workflows into software development and operations processes to ensure reliable, scalable and efficient deployment, monitoring and management of ML models in production. This episode is hosted by our Antonio Murgia. Don't forget to follow us on LinkedIn!
Transcribe →Data Contracts
Nov 22, 202400:53:33Tap to summarizeIn this Data Architecture Elevator episode, we’re diving into the world of data contracts—the unsung heroes of modern data management. We’ll explore how they’re reshaping collaboration between data producers and consumers, ensuring trust, accountability, and a clear understanding of responsibilities. Join us as we discuss common challenges, and reveal why data contracts are more than just tech jargon—they’re the foundation for a scalable, reliable, and efficient data-driven future. Our guests are Antonio Murgia and Ugo Ciracì, hosted by Paolo Platter. Let’s get started! 🚀
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