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2020-Q1 2026-Q1

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Coalesce 2024: Surfing the LLM wave: We can't opt out and neither can you

This session is a practical guide to changing how you operate in response to the Cambrian explosion of AI and LLM technologies. In your future, everyone at the company will have access to an LLM with unfettered access to your data warehouse. Do you feel afraid? The Data team at Hex did too. They'll share how they had to change how they worked to adapt, and what data leaders and practitioners need to be thinking about for their own teams.

Speakers: Amanda Fioritto Senior Analytics Engineer Hex Technologies

Erika Pullum Analytics Engineer Hex Technologies

Read the blog to learn about the latest dbt Cloud features announced at Coalesce, designed to help organizations embrace analytics best practices at scale https://www.getdbt.com/blog/coalesce-2024-product-announcements

Coalesce 2024: From Core to Cloud: Unlocking dbt at Warner Brothers Discovery (CNN)

Since the beginning of 2024, the Warner Brothers Discovery team supporting the CNN data platform has been undergoing an extensive migration project from dbt Core to dbt Cloud. Concurrently, the team is also segmenting their project into multi-project frameworks utilizing dbt Mesh. In this talk, Zachary will review how this transition has simplified data pipelines, improved pipeline performance and data quality, and made data collaboration at scale more seamless.

He'll discuss how dbt Cloud features like the Cloud IDE, automated testing, documentation, and code deployment have enabled the team to standardize on a single developer platform while also managing dependencies effectively. He'll share details on how the automation framework they built using Terraform streamlines dbt project deployments with dbt Cloud to a ""push-button"" process. By leveraging an infrastructure as code experience, they can orchestrate the creation of environment variables, dbt Cloud jobs, Airflow connections, and AWS secrets with a unified approach that ensures consistency and reliability across projects.

Speakers: Mamta Gupta Staff Analytics Engineer Warner Brothers Discovery

Zachary Lancaster Manager, Data Engineering Warner Brothers Discovery

Read the blog to learn about the latest dbt Cloud features announced at Coalesce, designed to help organizations embrace analytics best practices at scale https://www.getdbt.com/blog/coalesce-2024-product-announcements

Coalesce 2024: Why analytics engineering and DevOps go hand-in-hand

There are undoubtedly similarities between the disciplines of analytics engineering and DevOps: in fact, dbt was founded with the goal of helping data professionals embrace DevOps principles as part of the data workflow. As the embedded DevOps engineer for a mature analytics engineering function, Katie Claiborne, Founding Analytics Engineer at Duet, observed parallels between analytics-as-code and infrastructure-as-code, particularly tools like Terraform. In this talk, she'll examine how analytics engineering is a means of empowerment for data practitioners and discuss infrastructure engineering as a means of scaling dbt Cloud deployments. Learn about similarities between analytics and infrastructure configuration tools, how to apply the concepts you've learned about analytics engineering towards new disciplines like DevOps, and how to extend engineering principles beyond data transformation and into the world of infrastructure.

Speaker: Katie Claiborne Founding Analytics Engineer Duet

Read the blog to learn about the latest dbt Cloud features announced at Coalesce, designed to help organizations embrace analytics best practices at scale https://www.getdbt.com/blog/coalesce-2024-product-announcements

Coalesce 2024: Securing data access with dbt lineage and dbt grants

Carta prioritizes ensuring that their data is accessible only to the right individuals. Previously, they used functional groups to manage data access, but this approach often fell short in perfectly governing granular data sets. Recently, Carta developed a new access management system utilizing dbt lineage and dbt grants. These tools enable them to automatically propagate data access tags defined in dbt sources. This innovative system allows them to confidently ensure that individuals have appropriate access to data.

Speaker: Marco Albuquerque Senior Engineering Manager - Data Engineering Carta

Read the blog to learn about the latest dbt Cloud features announced at Coalesce, designed to help organizations embrace analytics best practices at scale https://www.getdbt.com/blog/coalesce-2024-product-announcements

Coalesce 2024: How SurveyMonkey sharpens dbt performance and governance with data observability

The data team at SurveyMonkey, the global leader in survey software, oversees heavy data transformation in dbt Cloud — both to power current business-critical projects, and also to migrate legacy workloads. Much of that transformation work is taking raw data — either from legacy databases or their cloud data warehouse (Snowflake) — and making it accessible and useful for downstream users. And to Samiksha Gour, Senior Data Engineering Manager at SurveyMonkey, each of these projects is not considered complete unless the proper checks, monitors, and alerts are in place.

Join Samiksha in this informative session as she walks through how her team uses dbt and their data observability platform Monte Carlo to ensure proper governance, gain efficiencies by eliminating duplicate testing and monitoring, and use data lineage to ensure upstream and downstream continuity for users and stakeholders.

Speaker: Samiksha Gour Senior Data Engineering Manager SurveyMonkey

Read the blog to learn about the latest dbt Cloud features announced at Coalesce, designed to help organizations embrace analytics best practices at scale https://www.getdbt.com/blog/coalesce-2024-product-announcements

Coalesce 2024: How Virgin Media O2 streamlines operations with dbt Cloud

Learn how Virgin Media O2 uses dbt Cloud to enhance call center efficiency, personalize customer communications, and accelerate data science workflows. In this session, we will share details about our innovative continuous flow system, developed using best practices from Toyota Kanban, and how it helps reduce operational waste and costs. We will also highlight a number of capabilities within dbt Cloud that support continuous data flows by automating manual tasks.

Read the blog to learn about the latest dbt Cloud features announced at Coalesce, designed to help organizations embrace analytics best practices at scale https://www.getdbt.com/blog/coalesce-2024-product-announcements

Speakers: Arun Kumaravel Senior Analytics Engineer Virgin Media O2

Oliver Burt Lead Analytics Engineer Virgin Media o2

Gordon Curzon Head of Analytics Engineering Virgin Media O2

Coalesce 2024: How to leverage dbt for embedded domain knowledge across product engineering teams

In today's data-driven world, harnessing the power of data is no longer an option but a necessity for businesses to thrive. For product engineering teams in particular, timely access to accurate and contextual data is crucial for making informed decisions and monitoring success. In this conversation, Aakriti Kaul and Scott Henry, Data Scientists at Cisco, dive into Duo Security’s data modernization journey, bolstered by dbt Cloud and embedded context in data, aimed at empowering product teams with data access and insights to drive innovation.

At the end of this session we hope to leave attendees with the following takeaways: • Understand how an Embedded Data science model creates value across Product, Engineering and Data teams • Learn practical strategies for implementing dbt within product development workflows to accelerate decision making and drive innovation, in partnership with Analytics Engineering teams • Gain insights from real-world case studies of Duo’s Product Data teams that have successfully leveraged dbt to provide access to data and insights for product teams • Gain insights from our organizational experience using dbt to provide product teams with self-service access to contextual datasets

The presentation is designed for data scientists, analytics engineers and other professionals involved in product development who are interested in leveraging data to drive decision making and embedding context within their data workflows. Whether you're new to dbt or looking to optimize your existing data analytics workflows, this session will provide valuable insights and practical strategies for harnessing the power of dbt in partnership with product engineering teams.

Speakers: Aakriti Kaul Data Scientist Duo Security @ Cisco

Scott Henry Data Scientist Duo Security @ Cisco

Read the blog to learn about the latest dbt Cloud features announced at Coalesce, designed to help organizations embrace analytics best practices at scale https://www.getdbt.com/blog/coalesce-2024-product-announcements

Coalesce 2024 Keynote: Turning data to value - A dbt customer panel

What does it mean to be successful with AI? Is it validating that it could prove long term value? Finding a way to innovate faster than before? And what role does dbt play in unlocking AI’s potential? dbt Labs COO Brandon Sweeney is joined by Fifth Third Bank and Optum UHG to talk about AI and the role dbt plays in accelerating business growth.

Read the blog to learn about the latest dbt Cloud features announced at Coalesce, designed to help organizations embrace analytics best practices at scale https://www.getdbt.com/blog/coalesce-2024-product-announcements

Coalesce 2024 Keynote: Innovating with dbt
video
by Roxi Dahlke (dbt Labs) , Yannick Misteli (Roche) , Tobias Humpert (Siemens AG) , Tristan Handy (dbt Labs) , Amy Chen (Fishtown Analytics) , Greg McKeon (dbt Labs) , James Dorado (Bilt Rewards)

dbt Labs co-founder and CEO, Tristan Handy, unveils his vision for the analytics development lifecycle, highlighting how our mission to make data and AI more accessible and trustworthy is fueling innovation. Hear from data leaders who have unlocked incredible business value with dbt Cloud at scale, and get an exclusive look at the groundbreaking product features that are launching soon. And remember, what happens in Vegas could change the future of analytics and AI.

Read the blog to learn more about the product announcements: https://www.getdbt.com/blog/coalesce-2024-product-announcements

Speakers: Tristan Handy Founder & CEO dbt Labs

Amy Chen Product Manager dbt Labs

Greg McKeon Staff Product Manager dbt Labs

Roxi Dahlke Product Manager dbt Labs

James Dorado VP, Data Analytics Bilt Rewards

Tobias Humpert Siemens Data Cloud Product Owner Siemens AG

Yannick Misteli Head of Engineering Roche

Send us a text Mr. Ian Smith, the most interesting man alive… Serial Entrepreneurial andCo-founder of Lighthouse Technology, accelerating AI in the data center to optimize IT, Cloud and Data environments.

00:58 Meet Ian Smith 03:24 Knowing when to Walk Away 06:32 Back to Ian 08:14 Startup Companies 09:51 A Wine Making Distraction 14:54 Exercise? 16:01 Back to Exciting Tech 19:12 Lighthouse Technology 26:46 Optimize Cloud via Conversational AI

Linkedin: linkedin.com/in/ian-smith-a803701 Website: https://lighthousetechnology.ai/

Want to be featured as a guest on Making Data Simple? Reach out to us [email protected] and tell us why you should be next. TheMaking Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales,IBM, where we explore trending technologies, business innovation, andleadership ... while keeping it simple & fun. Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Data Engineering Best Practices

Unlock the secrets to building scalable and efficient data architectures with 'Data Engineering Best Practices.' This book provides in-depth guidance on designing, implementing, and optimizing cloud-based data pipelines. You will gain valuable insights into best practices, agile workflows, and future-proof designs. What this Book will help me do Effectively plan and architect scalable data solutions leveraging cloud-first strategies. Master agile processes tailored to data engineering for improved project outcomes. Implement secure, efficient, and reliable data pipelines optimized for analytics and AI. Apply real-world design patterns and avoid common pitfalls in data flow and processing. Create future-ready data engineering solutions following industry-proven frameworks. Author(s) Richard J. Schiller and David Larochelle are seasoned data engineering experts with decades of experience crafting efficient and secure cloud-based infrastructures. Their collaborative writing distills years of real-world expertise into practical advice aimed at helping engineers succeed in a rapidly evolving field. Who is it for? This book is ideal for data engineers, ETL specialists, and big data professionals seeking to enhance their knowledge in cloud-based solutions. Some familiarity with data engineering, ETL pipelines, and big data technologies is helpful. It suits those keen on mastering advanced practices, improving agility, and developing efficient data pipelines. Perfect for anyone looking to future-proof their skills in data engineering.

Azure SQL Revealed: The Next-Generation Cloud Database with AI and Microsoft Fabric

Access detailed content and examples on Azure SQL, a set of cloud services that allows for SQL Server to be deployed in the cloud. This book teaches the fundamentals of deployment, configuration, security, performance, and availability of Azure SQL from the perspective of these same tasks and capabilities in SQL Server. This distinct approach makes this book an ideal learning platform for readers familiar with SQL Server on-premises who want to migrate their skills toward providing cloud solutions to an enterprise market that is increasingly cloud-focused. If you know SQL Server, you will love this book. You will be able to take your existing knowledge of SQL Server and translate that knowledge into the world of cloud services from the Microsoft Azure platform, and in particular into Azure SQL. This book provides information never seen before about the history and architecture of Azure SQL. Author Bob Ward is a leading expert with access to and support from the Microsoft engineering team that built Azure SQL and related database cloud services. He presents powerful, behind-the-scenes insights into the workings of one of the most popular database cloud services in the industry. This book also brings you the latest innovations for Azure SQL including Azure Arc, Hyperscale, generative AI applications, Microsoft Copilots, and integration with the Microsoft Fabric. What You Will Learn Know the history of Azure SQL Deploy, configure, and connect to Azure SQL Choose the correct way to deploy SQL Server in Azure Migrate existing SQL Server instances to Azure SQL Monitor and tune Azure SQL’s performance to meet your needs Ensure your data and application are highly available Secure your data from attack and theft Learn the latest innovations for Azure SQL including Hyperscale Learn how to harness the power of AI for generative data-driven applications and Microsoft Copilots for assistance Learn how to integrate Azure SQL with the unified data platform, the Microsoft Fabric Who This Book Is For This book is designed to teach SQL Server in the Azure cloud to the SQL Server professional. Anyone who operates, manages, or develops applications for SQL Server will benefit from this book. Readers will be able to translate their current knowledge of SQL Server—especially of SQL Server 2019 and 2022—directly to Azure. This book is ideal for database professionals looking to remain relevant as their customer base moves into the cloud.

The Data Product Management In Action podcast, brought to you by Soda and executive producer Scott Hirleman, is a platform for data product management practitioners to share insights and experiences.  In Season 01, Episode 19, host Nadiem von Heydebrand interviews Pradeep Fernando, who leads the data and metadata management initiative at Swisscom. They explore key topics in data product management, including the definition and categorization of data products, the role of AI, prioritization strategies, and the application of product management principles. Pradeep shares valuable insights and experiences on successfully implementing data product management within organizations. About our host Nadiem von Heydebrand: Nadiem is the CEO and Co-Founder of Mindfuel. In 2019, he merged his passion for data science with product management, becoming a thought leader in data product management. Nadiem is dedicated to demonstrating the true value contribution of data. With over a decade of experience in the data industry, Nadiem leverages his expertise to scale data platforms, implement data mesh concepts, and transform AI performance into business performance, delighting consumers at global organizations that include Volkswagen, Munich Re, Allianz, Red Bull, and Vorwerk. Connect with Nadiem on LinkedIn. About our guest Pradeep Fernando: Pradeep is a seasoned data product leader with over 6 years of data product leadership experience and over 10 years of product management experience. He leads or is a key contributor to several company-wide data & analytics initiatives at Swisscom such as Data as a Product (Data Mesh), One Data Platform, Machine Learning (Factory), MetaData management, Self-service data & analytics, BI Tooling Strategy, Cloud Transformation, Big Data platforms,and Data warehousing. Previously, he was a product manager at both Swisscom's B2B and Innovation units both building new products and optimizing mature products (profitability) in the domains of enterprise mobile fleet management, cyber-and mobile device security.Pradeep is also passionate about and experienced in leading the development of data products and transforming IT delivery teams into empowered, agile product teams. And, he is always happy to engage in a conversation about lean product management or "heavier" topics such as humanity's future or our past. Connect with Pradeep on LinkedIn. All views and opinions expressed are those of the individuals and do not necessarily reflect their employers or anyone else.  Join the conversation on LinkedIn.  Apply to be a guest or nominate someone that you know.  Do you love what you're listening to? Please rate and review the podcast, and share it with fellow practitioners you know. Your support helps us reach more listeners and continue providing valuable insights!              

Computational Intelligence in Sustainable Computing and Optimization

Computational Intelligence in Sustainable Computing and Optimization: Trends and Applications focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in applications, such as agriculture, biomedical systems, bioinformatics, business intelligence, economics, disaster management, e-learning, education management, financial management, and environmental policies. The book presents research in sustainable computing and optimization, combining methods from engineering, mathematics, artificial intelligence, and computer science to optimize environmental resources Computational intelligence in the field of sustainable computing combines computer science and engineering in applications ranging from Internet of Things (IoT), information security systems, smart storage, cloud computing, intelligent transport management, cognitive and bio-inspired computing, and management science. In addition, data intelligence techniques play a critical role in sustainable computing. Recent advances in data management, data modeling, data analysis, and artificial intelligence are finding applications in energy networks and thus making our environment more sustainable. Presents computational, intelligence–based data analysis for sustainable computing applications such as pattern recognition, biomedical imaging, sustainable cities, sustainable transport, sustainable agriculture, and sustainable financial management Develops research in sustainable computing and optimization, combining methods from engineering, mathematics, and computer science to optimize environmental resources Includes three foundational chapters dedicated to providing an overview of computational intelligence and optimization techniques and their applications for sustainable computing

Platform Engineering

Until recently, infrastructure was the backbone of organizations operating software they developed in-house. But now that cloud vendors run the computers, companies can finally bring the benefits of agile custom-centricity to their own developers. Adding product management to infrastructure organizations is now all the rage. But how's that possible when infrastructure is still the operational layer of the company? This practical book guides engineers, managers, product managers, and leaders through the shifts that modern platform-led organizations require. You'll learn what platform engineering is—and isn't—and what benefits and value it brings to developers and teams. You'll understand what it means to approach a platform as a product and learn some of the most common technical and managerial barriers to success. With this book, you'll: Cultivate a platform-as-product, developer-centric mindset Learn what platform engineering teams are and are not Start the process of adopting platform engineering within your organization Discover what it takes to become a product manager for a platform team Understand the challenges that emerge when you scale platforms Automate processes and self-service infrastructure to speed development and improve developer experience Build out, hire, manage, and advocate for a platform team

Take Control of Securing Your Apple Devices

Keep your Mac, iPhone, and iPad safe! Version 1.1.1, published September 28, 2025 Secure your Mac, iPhone, or iPad against attacks from the internet, physical intrusion, and more with the greatest of ease. Glenn Fleishman guides you through protecting yourself from phishing, email, and other exploits, as well as network-based invasive behavior. Learn about built-in privacy settings, the Secure Enclave, FileVault, hardware encryption keys, sandboxing, privacy settings, Advanced Data Protection, Lockdown Mode, resetting your password when all hope seems lost, and much more. The digital world is riddled with danger, even as Apple has done a fairly remarkable job at keeping our Macs, iPhones, and iPads safe. But the best security strategy is staying abreast of past risks and anticipating future ones. This book gives you all the insight and directions you need to ensure your Apple devices and their data are safe. It's up to date with macOS 26 Tahoe, iOS 26, and iPadOS 26. You’ll learn about the enhanced Advanced Data Protection option for iCloud services, allowing you to keep all your private data inaccessible not just to thieves and unwarranted government intrusion, but even to Apple! Also get the rundown on Lockdown Mode to deter direct network and phishing attacks, passkeys and hardware secure keys for the highest level of security for Apple Account and website logins, and Mac-specific features such as encrypted startup volumes and FileVault’s login protection process. Security and privacy are tightly related, and this book helps you understand how macOS, iOS, and iPadOS have increasingly compartmentalized and protected your personal data, and how to allow only the apps you want to access specific folders, your contacts, and other information. Here’s what this book has to offer:

Master the privacy settings on your Mac, iPhone, and iPad Calculate your level of risk and your tolerance for it Use Apple’s Stolen Device Protection feature for iPhone that deflects thieves who extract your passcode through coercion or misdirection. Learn why you’re asked to give permission for apps to access folders and personal data on your Mac Moderate access to your audio, video, screen actions, and other hardware inputs and outputs Get to know the increasing layers of system security deployed over the past few years Prepare against a failure or error that might lock you out of your device Share files and folders securely over a network and through cloud services Upgrade your iCloud data protection to use end-to-end encryption Control other low-level security options to reduce the risk of someone gaining physical access to your Mac—or override them to install system extensions Understand FileVault encryption and protection for Mac, and avoid getting locked out Investigate the security of a virtual private network (VPN) to see whether you should use one Learn how the Secure Enclave in Macs with a T2 chip or M-series Apple silicon affords hardware-level protections Dig into ransomware, the biggest potential threat to Mac users (though rare in practice) Discover recent security and privacy technologies, such as Lockdown Mode and passkeys Learn why your iPhone may restart automatically if it's been idle for several days

Data Engineering for Machine Learning Pipelines: From Python Libraries to ML Pipelines and Cloud Platforms

This book covers modern data engineering functions and important Python libraries, to help you develop state-of-the-art ML pipelines and integration code. The book begins by explaining data analytics and transformation, delving into the Pandas library, its capabilities, and nuances. It then explores emerging libraries such as Polars and CuDF, providing insights into GPU-based computing and cutting-edge data manipulation techniques. The text discusses the importance of data validation in engineering processes, introducing tools such as Great Expectations and Pandera to ensure data quality and reliability. The book delves into API design and development, with a specific focus on leveraging the power of FastAPI. It covers authentication, authorization, and real-world applications, enabling you to construct efficient and secure APIs using FastAPI. Also explored is concurrency in data engineering, examining Dask's capabilities from basic setup to crafting advanced machine learning pipelines. The book includes development and delivery of data engineering pipelines using leading cloud platforms such as AWS, Google Cloud, and Microsoft Azure. The concluding chapters concentrate on real-time and streaming data engineering pipelines, emphasizing Apache Kafka and workflow orchestration in data engineering. Workflow tools such as Airflow and Prefect are introduced to seamlessly manage and automate complex data workflows. What sets this book apart is its blend of theoretical knowledge and practical application, a structured path from basic to advanced concepts, and insights into using state-of-the-art tools. With this book, you gain access to cutting-edge techniques and insights that are reshaping the industry. This book is not just an educational tool. It is a career catalyst, and an investment in your future as a data engineering expert, poised to meet the challenges of today's data-driven world. What You Will Learn Elevate your data wrangling jobs by utilizing the power of both CPU and GPU computing, and learn to process data using Pandas 2.0, Polars, and CuDF at unprecedented speeds Design data validation pipelines, construct efficient data service APIs, develop real-time streaming pipelines and master the art of workflow orchestration to streamline your engineering projects Leverage concurrent programming to develop machine learning pipelines and get hands-on experience in development and deployment of machine learning pipelines across AWS, GCP, and Azure Who This Book Is For Data analysts, data engineers, data scientists, machine learning engineers, and MLOps specialists