As data workloads grow in complexity, teams need seamless orchestration to manage pipelines across batch, streaming, and AI/ML workflows. Apache Airflow provides a flexible and open-source way to orchestrate Databricks’ entire platform, from SQL analytics with Materialized Views (MVs) and Streaming Tables (STs) to AI/ML model training and deployment. In this session, we’ll showcase how Airflow can automate and optimize Databricks workflows, reducing costs and improving performance for large-scale data processing. We’ll highlight how MVs and STs eliminate manual incremental logic, enable real-time ingestion, and enhance query performance—all while maintaining governance and flexibility. Additionally, we’ll demonstrate how Airflow simplifies ML model lifecycle management by integrating Databricks’ AI/ML capabilities into end-to-end data pipelines. Whether you’re a dbt user seeking better performance, a data engineer managing streaming pipelines, or an ML practitioner scaling AI workloads, this session will provide actionable insights on using Airflow and Databricks together to build efficient, cost-effective, and future-proof data platforms.

This talk explores EDB’s journey from siloed reporting to a unified data platform, powered by Airflow. We’ll delve into the architectural evolution, showcasing how Airflow orchestrates a diverse range of use cases, from Analytics Engineering to complex MLOps pipelines. Learn how EDB leverages Airflow and Cosmos to integrate dbt for robust data transformations, ensuring data quality and consistency. We’ll provide a detailed case study of our MLOps implementation, demonstrating how Airflow manages training, inference, and model monitoring pipelines for Azure Machine Learning models. Discover the design considerations driven by our internal data governance framework and gain insights into our future plans for AIOps integration with Airflow.

As a popular open-source library for analytics engineering, dbt is often combined with Airflow. Orchestrating and executing dbt models as DAGs ensures an additional layer of control over tasks, observability, and provides a reliable, scalable environment to run dbt models. This workshop will cover a step-by-step guide to Cosmos , a popular open-source package from Astronomer that helps you quickly run your dbt Core projects as Airflow DAGs and Task Groups, all with just a few lines of code. We’ll walk through: Running and visualising your dbt transformations Managing dependency conflicts Defining database credentials (profiles) Configuring source and test nodes Using dbt selectors Customising arguments per model Addressing performance challenges Leveraging deferrable operators Visualising dbt docs in the Airflow UI Example of how to deploy to production Troubleshooting We encourage participants to bring their dbt project to follow this step-by-step workshop.

Trino is incredibly effective at enabling users to extract insights quickly and effectively from large amount of data located in dispersed and heterogeneous federated data systems. However, some business data problems are more complex than interactive analytics use cases, and are best broken down into a sequence of interdependent steps, a.k.a. a workflow. For these use cases, dedicated software is often required in order to schedule and manage these processes with a principled approach. In this session, we will look at how we can leverage Apache Airflow to orchestrate Trino queries into complex workflows that solve practical batch processing problems, all the while avoiding the use of repetitive, redundant data movement.

On March 13th, 2025, Amazon Web Services announced General Availability of Amazon SageMaker Unified Studio, bringing together AWS machine learning and analytics capabilities. At the heart of this next generation of Amazon SageMaker sits Apache Airflow. All SageMaker Unified Studio users have a personal, open-source Airflow deployment, running alongside their Jupyter notebook, enabling those users to easily develop Airflow DAGs that have unified access to all of their data. In this talk, I will go into details around the motivations for choosing Airflow for this capability, the challenges with incorporating Airflow into such a large and diverse experience, the key role that open-source plays, how we’re leveraging GenAI to make that open source development experience better, and the goals for the future of Airflow in SageMaker Unified Studio. Attendees will leave with a better understanding of the considerations they need to make when choosing Airflow as a component of their enterprise project, and a greater appreciation of how Airflow can power advanced capabilities.

Mark, Marisa, and colleague Adam Kamins are joined by Ivy Zelman to discuss the housing market outlook. Ivy sheds light on a wide variety of topics, including disappointing demand, the persistent drag from mortgage rate lock, and a lack of listings, adding up to a bearish outlook for prices and sales. The group also touches on regional differences, why builders are pulling back, and the effect of policy changes around tariffs and immigration. Along the way, Marisa and Adam learn the answers to a few existential questions, including “Why am I here?” Guest: Ivy Zelman, Executive Vice President of Zelman, a Walker & Dunlop Company Hosts: Mark Zandi – Chief Economist, Moody’s Analytics, Cris deRitis – Deputy Chief Economist, Moody’s Analytics, and Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody’s Analytics Follow Mark Zandi on 'X' and BlueSky @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn    

Questions or Comments, please email us at [email protected]. We would love to hear from you.    To stay informed and follow the insights of Moody's Analytics economists, visit Economic View.

What happens when AI becomes your coworker, not your replacement? In this episode, we sit down with Sadie St. Lawrence, founder of HMCI, to explore the rapidly evolving future of work, where AI isn't just a tool, but a teammate. We dig into how blue-collar and white-collar jobs will be shifting as AI and automation move from the periphery into our daily workflows. From analysts to factory floors, from dashboards to shop floors, what will it actually feel like to work alongside intelligent machines? Sadie also shares the deeply personal story of her 18-month journey exiting Women in Data, what she learned in building a global community, and how she's now thinking about the next wave of human + AI collaboration. If you're wondering what your job will look like in 5 years, this one's for you. What You'll Learn: What it really means to work with AI as a teammate How analysts can stay relevant in the age of automation The different futures ahead for blue- vs. white-collar roles How Sadie built, scaled, and thoughtfully exited Women in Data What makes a career resilient in an AI-driven economy   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

Rationale for Doris as a preferred infrastructure for AI-era analytics and search.

In this solo episode, Cynozure CEO Jason Foster explores what it really means to create value with data and AI and why it can't be treated as a nice-to-have outcome at the end of a project. Jason breaks down a practical, repeatable approach to designing value in from the start, with clear intent, strong foundations, and input-focused delivery. He shares real-world examples and analogies to show how organisations can shift from vague goals to measurable, meaningful impact. This episode is packed with actionable insights for data and business leaders who want to move from theory to practice and ensure their data work truly makes a difference.

Cynozure is a leading data, analytics and AI company that helps organisations to reach their data potential. It works with clients on data and AI strategy, data management, data architecture and engineering, analytics and AI, data culture and literacy, and data leadership. The company was named one of The Sunday Times' fastest-growing private companies in both 2022 and 2023 and recognised as The Best Place to Work in Data by DataIQ in 2023 and 2024. Cynozure is a certified B Corporation. 

Unlock the world of data science—no coding required. Curious about data science but not sure where to start? This book is a beginner-friendly guide to what data science is and how people use it. It walks you through the essential topics—what data analysis involves, which skills are useful, and how terms like “data analytics” and “machine learning” connect—without getting too technical too fast. Data science isn’t just about crunching numbers, pulling data from a database, or running fancy algorithms. It’s about asking the right questions, understanding the process from start to finish, and knowing what’s possible (and what’s not). This book teaches you all of that, while also introducing important topics like ethics, privacy, and security—because working with data means thinking about people, too. Whether you're a student exploring new skills, a professional navigating data-driven decisions, or someone considering a career change, this book is your friendly gateway into the world of data science, one of today’s most exciting fields. No coding or programming experience? No problem. You'll build a solid foundation and gain the confidence to engage with data science concepts— just as AI and data become increasingly central to everyday life. What You Will Learn Grasp foundational statistics and how it matters in data analysis and data science Understand the data science project life cycle and how to manage a data science project Examine the ethics of working with data and its use in data analysis and data science Understand the foundations of data security and privacy Collect, store, prepare, visualize, and present data Identify the many types of machine learning and know how to gauge performance Prepare for and find a career in data science Who This Book is for A wide range of readers who are curious about data science and eager to build a strong foundation. Perfect for undergraduates in the early semesters of their data science degrees, as it assumes no prior programming or industry experience. Professionals will find particular value in the real-world insights shared through practitioner interviews. Business leaders can use it to better understand what data science can do for them and how their teams are applying it. And for career changers, this book offers a welcoming entry point into the field—helping them explore the landscape before committing to more intensive learning paths like degrees or boot camps.

In the rapidly evolving world of data and analytics, professionals face the challenge of navigating complex platforms in order to build more efficient solutions. Microsoft Fabric, hailed as Microsoft’s “biggest data product in history after SQL Server,” offers powerful capabilities but comes with a steep learning curve. The myriad of choices within Fabric can be overwhelming, with multiple ways to tackle tasks, not all of which are equally efficient. This book serves as a definitive roadmap to understanding Microsoft Fabric—and leveraging it to suit your needs. Authors Nikola Ilic and Ben Weissman demystify the core concepts and components necessary to build, manage, and administer robust data solutions within this game-changing product. Discover the core Microsoft Fabric components and understand key concepts and techniques for building a robust data platform Learn to apply Microsoft Fabric effectively in your day-to-day job Understand the concept of a lake-centric architecture Gain the skills to implement a scalable and efficient end-to-end analytics solution Manage and administer a Fabric tenant

Welcome to the Data & AI NXT Conference! 🎉 This year, we explore the next frontier in analytics: Agentic AI.

🔍 Next-Generation Agentic Analytics Artificial Intelligence is pushing analytics beyond static dashboards and reports. At this event, discover how next-gen AI Agents transform fragmented, siloed data, both historical and real-time, into optimized, actionable intelligence.

Learn how businesses are evolving from reactive analytics to self-improving decision systems that span the entire enterprise.

🗓️ Agenda & Chapters

0:00 Start 7:37 Opening 23:15 The Unseen Sportian’s Playbook: Redefining Sports through Data and AI | Leandro Mora 1:06:16 Ethical implications of self-driving intelligence | Avijeet Dutta, Dr Shivani Rai Gupta, Jyothish Jayaraman, and Andres Tenorio 1:59:54 Governance in the age of AI Agents | Roberto Contreras 2:48:11 Synthetic data, digital twins & the future of testing | Carla Molgora, Ana Lía Villarreal and Cristina Garita 3:44:34 Future of BI: from dashboards to autonomous intelligence | Nacho Vuotto, Esteban Bertuccio, Carlos Alarcón, and Sergio Soliz 4:43:02 Real-Time vs. historical: balancing speed and context | Daniel Esteban Vesga, Oscar Narvaez, Martin Sciarrillo, and Abraham Jacob Montoya 5:38:16 AI Agents and the future of Human-Tech | Almudena Claudio

🙌 Thanks for joining us! Don't forget to like, comment, and subscribe for more tech insights from Globant.

💚

Overview of how AI transforms analytics into a strategic asset, covering AI’s role in analytics, features of AI-powered analytics tools, real-world use cases, breaking down data silos, fostering an AI-driven decision-making culture, and future-proofing your business for the next era of AI-powered analytics.

Turn your current tasks into clear, resume-ready bullets that sound more data-focused 👉 Resume Transformer: https://datafairy.io/GMM2DJKWM9 Here's a realization you need to hear: You're a Data Analyst ALREADY. You're not as far away as you think you are. In this episode, I teach you how to reframe your everyday tasks (and mind) to showcase your existing data skills, along with some real-life examples from my bootcamp students! Also, I provide useful tips to enhance your LinkedIn profile and resume to attract more job opportunities! 💌 Join 10k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter 🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training 👩‍💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa 👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com/interviewsimulator ⌚ TIMESTAMPS 00:00 Introduction: You're a Data Analyst already! 02:16 #1: Sales Professionals 03:04 #2: Teachers 03:54 #3: Delivery Drivers 04:40 #4: Physical Therapists 05:24 #5: Parents 06:12 #6: Retail Workers 06:41 #7: Construction Workers 07:26 DataFairy.io Check out these episodes! The ONLY Framework to Become a Data Analyst in 2025 (SPN Method) 👉 https://datacareerpodcast.com/episode/141-the-only-framework-to-become-a-data-analyst-in-2025-spn-method Zero to Data Analyst: Tim Beecher’s Journey from Locksmith to Data 👉 https://datacareerpodcast.com/episode/81-zero-to-data-analyst-tim-beechers-journey-from-locksmith-to-data

This Math Teacher Became a Data Analyst in 50 Days w/ Alex Sanchez 👉 https://datacareerpodcast.com/episode/112-this-math-teacher-became-a-data-analyst-in-50-days-w-alex-sanchez

How This Delivery Driver Became a FAANG Data Analyst (Jen Hawkins) 👉 https://datacareerpodcast.com/episode/154-how-this-delivery-driver-became-a-faang-data-analyst-in-100-days-jen-hawkins

This Physical Therapist Became a Data Analyst AFTER a 20-Year Career (Melody Santos) 👉 https://datacareerpodcast.com/episode/160-she-became-a-data-analyst-after-a-20-year-career-in-physical-therapy-melody-santos

From Construction to Data Analytics (Jordan Temple's Story) 👉 https://datacareerpodcast.com/episode/79-from-construction-to-data-analytics-jordan-temples-story

🔗 CONNECT WITH AVERY 🎥 YouTube Channel: https://www.youtube.com/@averysmith 🤝 LinkedIn: https://www.linkedin.com/in/averyjsmith/ 📸 Instagram: https://instagram.com/datacareerjumpstart 🎵 TikTok: https://www.tiktok.com/@verydata 💻 Website: https://www.datacareerjumpstart.com Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more

If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa

In this season of the Analytics Engineering podcast, Tristan is digging deep into the world of developer tools and databases. There are few more widely used developer tools than Docker. From its launch back in 2013, Docker has completely changed how developers ship applications.  In this episode, Tristan talks to Solomon Hykes, the founder and creator of Docker. They trace Docker's rise from startup obscurity to becoming foundational infrastructure in modern software development. Solomon explains the technical underpinnings of containerization, the pivotal shift from platform-as-a-service to open-source engine, and why Docker's developer experience was so revolutionary.  The conversation also dives into his next venture Dagger, and how it aims to solve the messy, overlooked workflows of software delivery. Bonus: Solomon shares how AI agents are reshaping how CI/CD gets done and why the next revolution in DevOps might already be here. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering Podcast is sponsored by dbt Labs.

Colleagues Chris Lafakis and Steve Cochrane join Inside Economics to discuss how geopolitics is shaping the outlook and the risks to the U.S. and global economies. But first, the team reminisces about Steve’s 32 years as “employee 007” at the company and his upcoming retirement. Steve reveals his secrets for “managing up,” and Mark finds out he’s been managed all these years. The conversation then turns to U.S.-China relations and the risk of an oil price shock stemming from Israel’s attack on Iran last week.    Guest: Chris Lafakis, Director of Climate and Energy Economics, Moody's Analytics, Steve Cochrane, Director, Chief APAC Economist Hosts: Mark Zandi – Chief Economist, Moody’s Analytics, Cris deRitis – Deputy Chief Economist, Moody’s Analytics, and Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody’s Analytics Follow Mark Zandi on 'X' and BlueSky @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn

Questions or Comments, please email us at [email protected]. We would love to hear from you.    To stay informed and follow the insights of Moody's Analytics economists, visit Economic View.

As AI agents become more powerful and widely adopted, enterprises face a new challenge: how to build them on a foundation of trustworthy, AI-ready data that includes both structured and unstructured data. Unstructured data introduces new complexity for organizations already contending with large and growing volumes of data that is often distributed and disconnected, and from more information sources. In this episode, Stephanie Valarezo, Program Director, Product, from IBM Data Integration, shares how organizations can simplify and scale the integration, access and governance of unstructured and structured data. Explore how IBM is simplifying the enterprise data stack by empowering teams to integrate structured and unstructured data, using batch, real-time streaming, or replication techniques, while extending governance beyond the data layer to the AI agents themselves. Whether you're modernizing legacy infrastructure, accelerating agent development, or building robust governance strategies, this session will give you a blueprint to: Unlock the value of unstructured data for enterprise-grade AI Accelerate data intelligence through built-in observability and governance Simplify your tech stack while improving trust and traceability in AI outputs Learn more about watsonx #sponsored   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

Samim Ghamami, Senior Economist at the U.S. Securities and Exchange Commission, joins Mark, Cris, and Marisa to explore the rapid rise of the private credit market. With global assets surpassing $2 trillion, Samim breaks down the systemic risks posed by this opaque yet fast-growing asset class. The discussion delves into private credit’s role in middle-market lending, private equity, and new markets like infrastructure and real estate, as well as its implications for financial stability and regulation. Access the full paper, Private Credit & Systemic Risk here: https://www.economy.com/getfile?q=2107637A-C535-4AFF-83BC-6CBA1AD1FAB9&app=download Guest: Samim Ghamami, Senior Economist at the Securities and Exchange Commission Hosts: Mark Zandi – Chief Economist, Moody’s Analytics, Cris deRitis – Deputy Chief Economist, Moody’s Analytics, Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody’s Analytics Follow Mark Zandi on 'X', BlueSky or LinkedIn @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn

Questions or Comments, please email us at [email protected]. We would love to hear from you.    To stay informed and follow the insights of Moody's Analytics economists, visit Economic View.

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Supported by Our Partners •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more. • Graphite — The AI developer productivity platform.  • Augment Code — AI coding assistant that pro engineering teams love — GitHub recently turned 17 years old—but how did it start, how has it evolved, and what does the future look like as AI reshapes developer workflows? In this episode of The Pragmatic Engineer, I’m joined by Thomas Dohmke, CEO of GitHub. Thomas has been a GitHub user for 16 years and an employee for 7. We talk about GitHub’s early architecture, its remote-first operating model, and how the company is navigating AI—from Copilot to agents. We also discuss why GitHub hires junior engineers, how the company handled product-market fit early on, and why being a beloved tool can make shipping harder at times. Other topics we discuss include: • How GitHub’s architecture evolved beyond its original Rails monolith • How GitHub runs as a remote-first company—and why they rarely use email  • GitHub’s rigorous approach to security • Why GitHub hires junior engineers • GitHub’s acquisition by Microsoft • The launch of Copilot and how it’s reshaping software development • Why GitHub sees AI agents as tools, not a replacement for engineers • And much more! — Timestamps (00:00) Intro (02:25) GitHub’s modern tech stack (08:11) From cloud-first to hybrid: How GitHub handles infrastructure (13:08) How GitHub’s remote-first culture shapes its operations (18:00) Former and current internal tools including Haystack (21:12) GitHub’s approach to security  (24:30) The current size of GitHub, including security and engineering teams (25:03) GitHub’s intern program, and why they are hiring junior engineers (28:27) Why AI isn’t a replacement for junior engineers  (34:40) A mini-history of GitHub  (39:10) Why GitHub hit product market fit so quickly  (43:44) The invention of pull requests (44:50) How GitHub enables offline work (46:21) How monetization has changed at GitHub since the acquisition  (48:00) 2014 desktop application releases  (52:10) The Microsoft acquisition  (1:01:57) Behind the scenes of GitHub’s quiet period  (1:06:42) The release of Copilot and its impact (1:14:14) Why GitHub decided to open-source Copilot extensions (1:20:01) AI agents and the myth of disappearing engineering jobs (1:26:36) Closing — The Pragmatic Engineer deepdives relevant for this episode: • AI Engineering in the real world • The AI Engineering stack •  How Linux is built with Greg Kroah-Hartman •  Stacked Diffs (and why you should know about them) •  50 Years of Microsoft and developer tools — See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠ — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].

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AI is having a huge impact, but is not the only thing with societal, technological, and organizational implications driving change in data and analytics. We examine trends in areas such as complexity, trust, and empowerment facing leaders and teams as they make decisions in all aspects of their bet-the-business D&A strategy.