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VS Code Day is our annual event where you'll learn how to elevate your development workflow with the latest and greatest features of VS Code. This year, we’re excited to delve into AI and you’ll hear from the VS Code team and other industry experts on topics like AI-powered programming with GitHub Copilot, building and deploying generative AI apps to the cloud, enhancing the C# development experience, and more. Whether you’re just starting out or you’re an experienced developer, join us on April 24, 2024 for a day focused on the editor that lets you code anything, cross-platform and free!

SESSIONS

• Welcome to VS Code Day 2024 with Gwyneth Peña-Siguenza and Reynald Adolphe
• View Source: What gets into VS Code and why with Burke Holland
• JavaScript developers: Build fast and have fun with VS Code and Azure AI CLI with Natalia Venditto
• Generating Synthetic Datasets with GitHub Copilot with Alfredo Deza
• Real World Development with VS Code and C# with Scott Hanselman and Leslie Richardson
• Building a RAG-powered AI chat app with Python and VS Code with Pamela Fox
• Beyond the Editor: Tips to get the Most out of GitHub Copilot with Kedasha Kerr
• LangChain Examples with Azure OpenAI Service + VS Code with Rishab Kumar
• AI Made Clear: Practical AI Coding Sessions in VS Code with Bruno Capuano
• Asking Copilot about your workspace with Matt Bierner

Pre-requisites: Resources we think you may find useful related to VS Code Day 2024:

• LinkedIn Clone Repo - https://aka.ms/linkedin-clone
• VS Code Day Cloud Skills Challenge - https://aka.ms/VSCodeDayChallenge

Summary

Five years of hosting the Data Engineering Podcast has provided Tobias Macey with a wealth of insight into the work of building and operating data systems at a variety of scales and for myriad purposes. In order to condense that acquired knowledge into a format that is useful to everyone Scott Hirleman turns the tables in this episode and asks Tobias about the tactical and strategic aspects of his experiences applying those lessons to the work of building a data platform from scratch.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management When you're ready to build your next pipeline, or want to test out the projects you hear about on the show, you'll need somewhere to deploy it, so check out our friends at Linode. With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Go to dataengineeringpodcast.com/linode today and get a $100 credit to launch a database, create a Kubernetes cluster, or take advantage of all of their other services. And don't forget to thank them for their continued support of this show! Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan's active metadata capabilities. Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value. Go to dataengineeringpodcast.com/atlan today to learn more about how Atlan’s active metadata platform is helping pioneering data teams like Postman, Plaid, WeWork & Unilever achieve extraordinary things with metadata and escape the chaos. Struggling with broken pipelines? Stale dashboards? Missing data? If this resonates with you, you’re not alone. Data engineers struggling with unreliable data need look no further than Monte Carlo, the leading end-to-end Data Observability Platform! Trusted by the data teams at Fox, JetBlue, and PagerDuty, Monte Carlo solves the costly problem of broken data pipelines. Monte Carlo monitors and alerts for data issues across your data warehouses, data lakes, dbt models, Airflow jobs, and business intelligence tools, reducing time to detection and resolution from weeks to just minutes. Monte Carlo also gives you a holistic picture of data health with automatic, end-to-end lineage from ingestion to the BI layer directly out of the box. Start trusting your data with Monte Carlo today! Visit dataengineeringpodcast.com/montecarlo to learn more. Your host is Tobias Macey and today I'm being interviewed by Scott Hirleman about my work on the podcasts and my experience building a data platform

Interview

Introduction How did you get involved in the area of data management?

Data platform building journey

Why are you building, who are the users/use cases How to focus on doing what matters over cool tools How to build a good UX Anything surprising or did you discover anything you didn't expect at the start How to build so it's modular and can be improved in the future

General build vs buy and vendor selection process

Obviously have a good BS detector - how can others build theirs So many tools, where do you start - capability need, vendor suite offering, etc. Anything surprising in doing much of this at once How do you think about TCO in build versus buy Any advice

Guest call out

Be brave, believe you are good enough to be on the show Look at past episodes and don't pitch the same as what's been on recently And vendors, be smart, work with your customers to come up with a good pitch for them as guests...

Tobias' advice and learnings from building out a data platform:

Advice: when considering a tool, start from what are you act

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