🌟 Session Overview 🌟

Session Name: LLMs for Self-serve Analytics - Lessons Learned Speaker: Thomas Schmidt Session Description: Thomas Schmidt will discuss lessons learned from using Large Language Models (LLMs) in self-serve analytics. He will explain why text-to-SQL alone is insufficient for Business Intelligence (BI) and highlight the limitations of simple chat interfaces. Additionally, Thomas will describe how specialized AI agents can autonomously solve complex analytical problems, offering a more effective BI solution.

🚀 About Big Data and RPA 2024 🚀

Unlock the future of innovation and automation at Big Data & RPA Conference Europe 2024! 🌟 This unique event brings together the brightest minds in big data, machine learning, AI, and robotic process automation to explore cutting-edge solutions and trends shaping the tech landscape. Perfect for data engineers, analysts, RPA developers, and business leaders, the conference offers dual insights into the power of data-driven strategies and intelligent automation. 🚀 Gain practical knowledge on topics like hyperautomation, AI integration, advanced analytics, and workflow optimization while networking with global experts. Don’t miss this exclusive opportunity to expand your expertise and revolutionize your processes—all from the comfort of your home! 📊🤖✨

📅 Yearly Conferences: Curious about the evolution of QA? Check out our archive of past Big Data & RPA sessions. Watch the strategies and technologies evolve in our videos! 🚀 🔗 Find Other Years' Videos: 2023 Big Data Conference Europe https://www.youtube.com/playlist?list=PLqYhGsQ9iSEpb_oyAsg67PhpbrkCC59_g 2022 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEryAOjmvdiaXTfjCg5j3HhT 2021 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEqHwbQoWEXEJALFLKVDRXiP

💡 Stay Connected & Updated 💡

Don’t miss out on any updates or upcoming event information from Big Data & RPA Conference Europe. Follow us on our social media channels and visit our website to stay in the loop!

🌐 Website: https://bigdataconference.eu/, https://rpaconference.eu/ 👤 Facebook: https://www.facebook.com/bigdataconf, https://www.facebook.com/rpaeurope/ 🐦 Twitter: @BigDataConfEU, @europe_rpa 🔗 LinkedIn: https://www.linkedin.com/company/73234449/admin/dashboard/, https://www.linkedin.com/company/75464753/admin/dashboard/ 🎥 YouTube: http://www.youtube.com/@DATAMINERLT

🌟 Session Overview 🌟

Session Name: Supernovas, Black Holes, and Streaming Data: A Journey in Space with Apache Kafka data streams from NASA Speaker: Frank Munz Session Description: In this fun, hands-on, and in-depth How-To, we explore NASA's GCN project, which publishes various events in space as Kafka topics.

The focus of my talk is on end-to-end data engineering, from consuming the data and ELT-ing the stream, to using generative AI tools for analytics.

We will analyze GCN data in real time, specifically targeting the data stream from exploding supernovas. This data triggers dozens of terrestrial telescopes to potentially reposition and point toward the event.

The speaker will kick off the session by contrasting various ways of ingesting and transforming the data, discussing their trade-offs: Should you use a declarative data pipeline, or can a data analyst manage with SQL only? Alternatively, when would it be better to follow the classic approach of orchestrating Spark notebooks to get the data ingested?

He will answer the question: Does a data engineer working with streaming data benefit from generative AI-based tools and assistants today? Is it worth it, or is it just hype?

The demo is easy to replicate at home, and Frank will share the notebooks in a GitHub repository so you can analyze real NASA data yourself!

This session is ideal for data engineers, data architects who enjoy some coding, generative AI enthusiasts, or anyone fascinated by technology and the sparkling stars in the night sky.

While the focus is clearly on tech, the demo will run on the open-source and open-standards-based Databricks Intelligence Platform (so inevitably, you'll get a high-level overview here too).

🚀 About Big Data and RPA 2024 🚀

Unlock the future of innovation and automation at Big Data & RPA Conference Europe 2024! 🌟 This unique event brings together the brightest minds in big data, machine learning, AI, and robotic process automation to explore cutting-edge solutions and trends shaping the tech landscape. Perfect for data engineers, analysts, RPA developers, and business leaders, the conference offers dual insights into the power of data-driven strategies and intelligent automation. 🚀 Gain practical knowledge on topics like hyperautomation, AI integration, advanced analytics, and workflow optimization while networking with global experts. Don’t miss this exclusive opportunity to expand your expertise and revolutionize your processes—all from the comfort of your home! 📊🤖✨

📅 Yearly Conferences: Curious about the evolution of QA? Check out our archive of past Big Data & RPA sessions. Watch the strategies and technologies evolve in our videos! 🚀 🔗 Find Other Years' Videos: 2023 Big Data Conference Europe https://www.youtube.com/playlist?list=PLqYhGsQ9iSEpb_oyAsg67PhpbrkCC59_g 2022 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEryAOjmvdiaXTfjCg5j3HhT 2021 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEqHwbQoWEXEJALFLKVDRXiP

💡 Stay Connected & Updated 💡

Don’t miss out on any updates or upcoming event information from Big Data & RPA Conference Europe. Follow us on our social media channels and visit our website to stay in the loop!

🌐 Website: https://bigdataconference.eu/, https://rpaconference.eu/ 👤 Facebook: https://www.facebook.com/bigdataconf, https://www.facebook.com/rpaeurope/ 🐦 Twitter: @BigDataConfEU, @europe_rpa 🔗 LinkedIn: https://www.linkedin.com/company/73234449/admin/dashboard/, https://www.linkedin.com/company/75464753/admin/dashboard/ 🎥 YouTube: http://www.youtube.com/@DATAMINERLT

🌟 Session Overview 🌟

Session Name: Data Engineers: Respect the Resiliency of SQL Speaker: Rui Machado Session Description: In the ever-evolving data landscape, SQL's resilience shines, powering critical systems across all industries. Despite new technologies, SQL's core definition and manipulation language remains indispensable, evolving to meet modern demands. This talk explores why SQL endures, spotlighting its integration in innovative tools like dbt and DuckDB, which leverage SQL interfaces for advanced data processing. It will reveal some of the secrets behind SQL's lasting popularity and its pivotal role in the future of data engineering.

🚀 About Big Data and RPA 2024 🚀

Unlock the future of innovation and automation at Big Data & RPA Conference Europe 2024! 🌟 This unique event brings together the brightest minds in big data, machine learning, AI, and robotic process automation to explore cutting-edge solutions and trends shaping the tech landscape. Perfect for data engineers, analysts, RPA developers, and business leaders, the conference offers dual insights into the power of data-driven strategies and intelligent automation. 🚀 Gain practical knowledge on topics like hyperautomation, AI integration, advanced analytics, and workflow optimization while networking with global experts. Don’t miss this exclusive opportunity to expand your expertise and revolutionize your processes—all from the comfort of your home! 📊🤖✨

📅 Yearly Conferences: Curious about the evolution of QA? Check out our archive of past Big Data & RPA sessions. Watch the strategies and technologies evolve in our videos! 🚀 🔗 Find Other Years' Videos: 2023 Big Data Conference Europe https://www.youtube.com/playlist?list=PLqYhGsQ9iSEpb_oyAsg67PhpbrkCC59_g 2022 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEryAOjmvdiaXTfjCg5j3HhT 2021 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEqHwbQoWEXEJALFLKVDRXiP

💡 Stay Connected & Updated 💡

Don’t miss out on any updates or upcoming event information from Big Data & RPA Conference Europe. Follow us on our social media channels and visit our website to stay in the loop!

🌐 Website: https://bigdataconference.eu/, https://rpaconference.eu/ 👤 Facebook: https://www.facebook.com/bigdataconf, https://www.facebook.com/rpaeurope/ 🐦 Twitter: @BigDataConfEU, @europe_rpa 🔗 LinkedIn: https://www.linkedin.com/company/73234449/admin/dashboard/, https://www.linkedin.com/company/75464753/admin/dashboard/ 🎥 YouTube: http://www.youtube.com/@DATAMINERLT

🌟 Session Overview 🌟

Session Name: Optimising Apache Spark and SQL for Improved Performance Speaker: Marcin Szymaniuk Session Description: Discover the diverse world of big data scenarios where Apache Spark shines. In 2023, while Spark has optimized its delivery, some elements still need a keen understanding and manual oversight. This is where Marcin comes in. After extensive testing and experimenting, he's pinpointed vital areas where your insight matters most, and he'll guide you through them all, case by case. Navigating the technical complexities of Apache Spark? No problem! Marcin will wrap up by delving into the finer details beyond SQL, presenting them in an easily digestible manner. Learn how to tackle your most pressing Apache Spark issues and optimize it for maximum business value.

Marcin is bringing you comprehensive solutions, demystifying the backend, and enabling you to harness the power of Spark without being an AI master. In a nutshell, he'll share top insights from TantusData's extensive experience with Apache Spark to help you steer clear of pitfalls—all in a single, engaging presentation. 🚀 About Big Data and RPA 2024 🚀

Unlock the future of innovation and automation at Big Data & RPA Conference Europe 2024! 🌟 This unique event brings together the brightest minds in big data, machine learning, AI, and robotic process automation to explore cutting-edge solutions and trends shaping the tech landscape. Perfect for data engineers, analysts, RPA developers, and business leaders, the conference offers dual insights into the power of data-driven strategies and intelligent automation. 🚀 Gain practical knowledge on topics like hyperautomation, AI integration, advanced analytics, and workflow optimization while networking with global experts. Don’t miss this exclusive opportunity to expand your expertise and revolutionize your processes—all from the comfort of your home! 📊🤖✨

📅 Yearly Conferences: Curious about the evolution of QA? Check out our archive of past Big Data & RPA sessions. Watch the strategies and technologies evolve in our videos! 🚀 🔗 Find Other Years' Videos: 2023 Big Data Conference Europe https://www.youtube.com/playlist?list=PLqYhGsQ9iSEpb_oyAsg67PhpbrkCC59_g 2022 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEryAOjmvdiaXTfjCg5j3HhT 2021 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEqHwbQoWEXEJALFLKVDRXiP

💡 Stay Connected & Updated 💡

Don’t miss out on any updates or upcoming event information from Big Data & RPA Conference Europe. Follow us on our social media channels and visit our website to stay in the loop!

🌐 Website: https://bigdataconference.eu/, https://rpaconference.eu/ 👤 Facebook: https://www.facebook.com/bigdataconf, https://www.facebook.com/rpaeurope/ 🐦 Twitter: @BigDataConfEU, @europe_rpa 🔗 LinkedIn: https://www.linkedin.com/company/73234449/admin/dashboard/, https://www.linkedin.com/company/75464753/admin/dashboard/ 🎥 YouTube: http://www.youtube.com/@DATAMINERLT

🌟 Session Overview 🌟

Session Name: SQL from the Frontend: Viable or Not? Speaker: David Gomes Session Description: David has worked on apps with a “SQL from the client” architecture, and the development velocity was simply superb. At the same time, it comes with many challenges, particularly in terms of security and scalability. So, what’s the deal? Is it viable or not?

The tl;dr is that the technology is perhaps not ready yet, but it makes a lot of sense for a large swath of apps – especially for prototypes. However, this is a complex topic, and I’ll delve deeper into the security problems during this talk. 🚀 About Big Data and RPA 2024 🚀

Unlock the future of innovation and automation at Big Data & RPA Conference Europe 2024! 🌟 This unique event brings together the brightest minds in big data, machine learning, AI, and robotic process automation to explore cutting-edge solutions and trends shaping the tech landscape. Perfect for data engineers, analysts, RPA developers, and business leaders, the conference offers dual insights into the power of data-driven strategies and intelligent automation. 🚀 Gain practical knowledge on topics like hyperautomation, AI integration, advanced analytics, and workflow optimization while networking with global experts. Don’t miss this exclusive opportunity to expand your expertise and revolutionize your processes—all from the comfort of your home! 📊🤖✨

📅 Yearly Conferences: Curious about the evolution of QA? Check out our archive of past Big Data & RPA sessions. Watch the strategies and technologies evolve in our videos! 🚀 🔗 Find Other Years' Videos: 2023 Big Data Conference Europe https://www.youtube.com/playlist?list=PLqYhGsQ9iSEpb_oyAsg67PhpbrkCC59_g 2022 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEryAOjmvdiaXTfjCg5j3HhT 2021 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEqHwbQoWEXEJALFLKVDRXiP

💡 Stay Connected & Updated 💡

Don’t miss out on any updates or upcoming event information from Big Data & RPA Conference Europe. Follow us on our social media channels and visit our website to stay in the loop!

🌐 Website: https://bigdataconference.eu/, https://rpaconference.eu/ 👤 Facebook: https://www.facebook.com/bigdataconf, https://www.facebook.com/rpaeurope/ 🐦 Twitter: @BigDataConfEU, @europe_rpa 🔗 LinkedIn: https://www.linkedin.com/company/73234449/admin/dashboard/, https://www.linkedin.com/company/75464753/admin/dashboard/ 🎥 YouTube: http://www.youtube.com/@DATAMINERLT

Join this session to learn about the newest innovations in data warehousing and SQL analytics with AWS analytics services. Amazon Redshift is the AI-powered, cloud-based data warehousing solution used by tens of thousands of AWS customers to modernize data analytics workloads and generate business insights with the best price performance. Learn more about the latest capabilities launched for Amazon Redshift to further drive quick decision-making with lower costs for your organization.

Learn more: AWS re:Invent: https://go.aws/reinvent. More AWS events: https://go.aws/3kss9CP

Subscribe: More AWS videos: http://bit.ly/2O3zS75 More AWS events videos: http://bit.ly/316g9t4

About AWS: Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSreInvent2024

A practical introduction to data engineering on the powerful Snowflake cloud data platform. Data engineers create the pipelines that ingest raw data, transform it, and funnel it to the analysts and professionals who need it. The Snowflake cloud data platform provides a suite of productivity-focused tools and features that simplify building and maintaining data pipelines. In Snowflake Data Engineering, Snowflake Data Superhero Maja Ferle shows you how to get started. In Snowflake Data Engineering you will learn how to: Ingest data into Snowflake from both cloud and local file systems Transform data using functions, stored procedures, and SQL Orchestrate data pipelines with streams and tasks, and monitor their execution Use Snowpark to run Python code in your pipelines Deploy Snowflake objects and code using continuous integration principles Optimize performance and costs when ingesting data into Snowflake Snowflake Data Engineering reveals how Snowflake makes it easy to work with unstructured data, set up continuous ingestion with Snowpipe, and keep your data safe and secure with best-in-class data governance features. Along the way, you’ll practice the most important data engineering tasks as you work through relevant hands-on examples. Throughout, author Maja Ferle shares design tips drawn from her years of experience to ensure your pipeline follows the best practices of software engineering, security, and data governance. About the Technology Pipelines that ingest and transform raw data are the lifeblood of business analytics, and data engineers rely on Snowflake to help them deliver those pipelines efficiently. Snowflake is a full-service cloud-based platform that handles everything from near-infinite storage, fast elastic compute services, inbuilt AI/ML capabilities like vector search, text-to-SQL, code generation, and more. This book gives you what you need to create effective data pipelines on the Snowflake platform. About the Book Snowflake Data Engineering guides you skill-by-skill through accomplishing on-the-job data engineering tasks using Snowflake. You’ll start by building your first simple pipeline and then expand it by adding increasingly powerful features, including data governance and security, adding CI/CD into your pipelines, and even augmenting data with generative AI. You’ll be amazed how far you can go in just a few short chapters! What's Inside Ingest data from the cloud, APIs, or Snowflake Marketplace Orchestrate data pipelines with streams and tasks Optimize performance and cost About the Reader For software developers and data analysts. Readers should know the basics of SQL and the Cloud. About the Author Maja Ferle is a Snowflake Subject Matter Expert and a Snowflake Data Superhero who holds the SnowPro Advanced Data Engineer and the SnowPro Advanced Data Analyst certifications. Quotes An incredible guide for going from zero to production with Snowflake. - Doyle Turner, Microsoft A must-have if you’re looking to excel in the field of data engineering. - Isabella Renzetti, Data Analytics Consultant & Trainer Masterful! Unlocks the true potential of Snowflake for modern data engineers. - Shankar Narayanan, Microsoft Valuable insights will enhance your data engineering skills and lead to cost-effective solutions. A must read! - Frédéric L’Anglais, Maxa Comprehensive, up-to-date and packed with real-life code examples. - Albert Nogués, Danone

Amazon Redshift Serverless uses AI and ML to automatically provision and scale data warehouse capacity and deliver fast performance for demanding and unpredictable workloads. It delivers a first-class data sharing experience where you can isolate workloads and read from and write to the same Redshift databases to build multi-warehouse, data mesh architectures and simplify SQL analytics. Join this session to learn best practices and key considerations for data sharing and SQL analytics with Redshift Serverless to optimize price-performance for your most demanding analytics workloads.

Learn more: AWS re:Invent: https://go.aws/reinvent. More AWS events: https://go.aws/3kss9CP

Subscribe: More AWS videos: http://bit.ly/2O3zS75 More AWS events videos: http://bit.ly/316g9t4

About AWS: Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSreInvent2024

Self-service analytics empowers users to independently access, explore, and analyze data to accelerate decision-making. It’s a foundational step for organizations to democratize the use of data for business growth with easy-to-use, simple-to-understand, and quick-to-deliver tools. Interactive querying, SQL analytics, data preparation, data transformation, data workflow orchestration and search analytics are some of the key day-to-day functions that data users need from self-service solutions. Learn how AWS analytics services like Amazon Athena, AWS Glue, Amazon Redshift, Amazon Managed Workflows for Apache Airflow, and Amazon OpenSearch Service enable data-driven decision-making through self-serve analytics.

Learn more: AWS re:Invent: https://go.aws/reinvent. More AWS events: https://go.aws/3kss9CP

Subscribe: More AWS videos: http://bit.ly/2O3zS75 More AWS events videos: http://bit.ly/316g9t4

About AWS: Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSreInvent2024

PostgreSQL makes it easier to store and query vector data for artificial intelligence and machine learning (AI/ML) use cases with the pgvector extension. Learning best practices for vector search will help you deliver a high-performance experience to your customers. In this session, learn how to store data from Amazon Bedrock in an Amazon Aurora PostgreSQL-Compatible Edition database and learn SQL queries and tuning parameters to optimize the performance of your application when working with AI/ML data, vector data types, exact and approximate nearest neighbor search algorithms, and vector-optimized indexing.

Learn more: AWS re:Invent: https://go.aws/reinvent. More AWS events: https://go.aws/3kss9CP

Subscribe: More AWS videos: http://bit.ly/2O3zS75 More AWS events videos: http://bit.ly/316g9t4

About AWS: Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

AWSreInvent #AWSreInvent2024

In this session, we will explore the roadmap of SQL Server including future capabilities for AI applications deeply integrated into the security zone of the SQL Server engine. We will also show you AI assisted experiences to help you manage SQL Server including tools like SQL Server Management Studio (SSMS), Query Store, Intelligent Query Processing and Azure Arc. Learn how AI can streamline your workflow, reduce context switching, and boost overall efficiency.

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Joe Sack * Erin Stellato * Bob Ward

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Ignite 2024 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com

BRK195 | English (US) | Data

MSIgnite

GenAI applications and Copilots are transforming the SQL experience. Join us to learn how Microsoft delivers an optimal platform for new AI workloads using vectors and RAG patterns, while ensuring ROI, performance, and security your business demands today. Discover the latest innovations for Azure SQL for gen AI applications and database context-aware Copilots, powered by Azure SQL Database Hyperscale. Ensure your SQL estate is future-ready in this era of intelligent applications and analytics.

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * John Tracy * Bob Ward * Muazma Zahid

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Ignite 2024 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com

BRK192 | English (US) | Data

MSIgnite

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

Introducing SQL database in Fabric: Discover the future of data management and unlock new scenarios that drive your business forward. Join us as we showcase the first fully SaaS database experience in Microsoft Fabric. Experience the simplicity of an integrated development environment that empowers you to quickly harness the power of an AI-driven analytics platform. Learn how to access both transactional and analytical data in one place without compromising application performance.

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Panos/Panagiotis Antonopoulos * Anna Hoffman * Asad Khan

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Ignite 2024 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com

BRK196 | English (US) | Data

MSIgnite

Help us become the #1 Data Podcast by leaving a rating & review! We are 67 reviews away! No fluff, no jargon; just the essentials to kick-start your data analyst career in 2025 with a strategy built for success. 💌 Join 30k+ 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 00:16 Understanding Different Data Roles 01:48 Essential Data Skills and Tools 04:36 Building Projects to Showcase Skills 08:13 Creating a Portfolio for Your Projects 09:06 Optimizing LinkedIn and Resume 10:46 Applying for Jobs and Networking 12:38 Preparing for Interviews 14:25 Conclusion and Final Tips Join the Bootcamp: Data Career Jumpstart Browse Data Jobs: Find a Data Job Must-Learn Skills for Aspiring Analysts: Watch on YouTube Find Free Datasets for Practice: Watch on YouTube Stratascratch for SQL Practice: Visit Stratascratch Prepare for Interviews: Interview Simulator 🔗 CONNECT WITH AVERY 🎥 YouTube Channel 🤝 LinkedIn 📸 Instagram 🎵 TikTok 💻 Website 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

All the mistakes you might make with SQL Server—and how to avoid them! 100 SQL Server Mistakes and How to Avoid Them prepares you for the pitfalls database professionals often encounter—from administration to development, availability, and security. You'll learn to sidestep common errors that slow down your T-SQL code and ensure your SQL Server is installed and configured to handle anything your organization throws at it. Inside 100 SQL Server Mistakes and How to Avoid Them you'll learn to avoid: Development errors when writing T-SQL Installation and administration mistakes Optimization missteps Common pitfalls relating to high availability and disaster recovery (HA/DR) Security oversights that can endanger your data 100 SQL Server Mistakes and How to Avoid Them doesn't focus on the "happy path"—instead, it covers all the errors and problems you might face as a SQL Server developer or administrator. Each chapter is filled with real-world issues drawn from author Peter A. Carter’s two-decade-long career in SQL Server. Peter's seasoned advice helps dispel myths, debunk misconceptions, and set you on the right road. About the Technology Perfecting a SQL Server system can be a complex balancing act. Why is T-SQL running so slowly? Are the right data available? Are we protected against data theft? What about that new server instance I need to administer? Even the most skilled SQL Server experts make mistakes that cost time and performance. This book can help you get it right the first time. About the Book 100 SQL Server Mistakes and How to Avoid Them focuses exclusively on the errors that you might—and probably will—make as a SQL Server admin or developer. Real-world examples, code samples, and helpful diagrams make it easy to understand each issue and its solution. You’ll learn how to write performant code, design efficient database schemas, implement error handling, work with complex data types, and much more, all in a friendly, common-sense problem/solution format. What's Inside T-SQL development Installation, administration, and optimization High availability and security About the Reader Readers need to understand basic SQL Server concepts and SQL queries. Perfect for junior database admins, full-stack developers, and “accidental” DBAs. About the Author Peter A. Carter is a SQL Server expert with experience developing, administering, and architecting data-tier applications and SQL Server platforms. Quotes A masterful job! Covers the nuances of SQL Server that a new admin, or even an experienced one, needs to understand. - Allen White, SQL Server MVP 2007-2022 Quick, actionable advice that greatly improved my SQL Server skills. - Ruben Vandeginste, PeopleWare A practical path through pitfalls in administration and development with specific solutions, examples, and code snippets. - Josephine Bush, sqlkitty.com Worth reading for the testing and debugging section alone! - Mike McQuillan, McQTech Ltd.

Help us become the #1 Data Podcast by leaving a rating & review! We are 67 reviews away! For anyone aiming to break into data analysis, Avery’s roadmap is the ultimate guide. With practical advice and clear steps, this episode sets you up for success in just 100 days. 💌 Join 30k+ 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 01:06 AI Avatars Talk About the Plan 02:04 Learning About Data Roles 03:55 Getting Good at Excel 04:55 Visualizing Data with Tableau 05:54 Learning SQL Basics 06:58 Starting Job Prep Early 07:15 Applying for Jobs Smartly 09:27 Capstone Project: Showing Off Your Skills 11:22 Last Tips and Encouragement 🔗 CONNECT WITH AVERY 🎥 YouTube Channel 🤝 LinkedIn 📸 Instagram 🎵 TikTok 💻 Website 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!

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Summary The challenges of integrating all of the tools in the modern data stack has led to a new generation of tools that focus on a fully integrated workflow. At the same time, there have been many approaches to how much of the workflow is driven by code vs. not. Burak Karakan is of the opinion that a fully integrated workflow that is driven entirely by code offers a beneficial and productive means of generating useful analytical outcomes. In this episode he shares how Bruin builds on those opinions and how you can use it to build your own analytics without having to cobble together a suite of tools with conflicting abstractions.

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data managementImagine catching data issues before they snowball into bigger problems. That’s what Datafold’s new Monitors do. With automatic monitoring for cross-database data diffs, schema changes, key metrics, and custom data tests, you can catch discrepancies and anomalies in real time, right at the source. Whether it’s maintaining data integrity or preventing costly mistakes, Datafold Monitors give you the visibility and control you need to keep your entire data stack running smoothly. Want to stop issues before they hit production? Learn more at dataengineeringpodcast.com/datafold today!Your host is Tobias Macey and today I'm interviewing Burak Karakan about the benefits of building code-only data systemsInterview IntroductionHow did you get involved in the area of data management?Can you describe what Bruin is and the story behind it?Who is your target audience?There are numerous tools that address the ETL workflow for analytical data. What are the pain points that you are focused on for your target users?How does a code-only approach to data pipelines help in addressing the pain points of analytical workflows?How might it act as a limiting factor for organizational involvement?Can you describe how Bruin is designed?How have the design and scope of Bruin evolved since you first started working on it?You call out the ability to mix SQL and Python for transformation pipelines. What are the components that allow for that functionality?What are some of the ways that the combination of Python and SQL improves ergonomics of transformation workflows?What are the key features of Bruin that help to streamline the efforts of organizations building analytical systems?Can you describe the workflow of someone going from source data to warehouse and dashboard using Bruin and Ingestr?What are the opportunities for contributions to Bruin and Ingestr to expand their capabilities?What are the most interesting, innovative, or unexpected ways that you have seen Bruin and Ingestr used?What are the most interesting, unexpected, or challenging lessons that you have learned while working on Bruin?When is Bruin the wrong choice?What do you have planned for the future of Bruin?Contact Info LinkedInParting Question From your perspective, what is the biggest gap in the tooling or technology for data management today?Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.init covers the Python language, its community, and the innovative ways it is being used. The AI Engineering Podcast is your guide to the fast-moving world of building AI systems.Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.If you've learned something or tried out a project from the show then tell us about it! Email [email protected] with your story.Links BruinFivetranStitchIngestrBruin CLIMeltanoSQLGlotdbtSQLMeshPodcast EpisodeSDFPodcast EpisodeAirflowDagsterSnowparkAtlanEvidenceThe intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

For years, Data Analysts and Data Scientists have been two of the most in-demand roles. In this show, Chris Bruehl and Alice Zhao will talk about the similarities and differences between the two roles, potential career paths, and their thoughts on how you can decide which flavor of data role is a better fit for you. You'll leave the show with a deeper understanding of these two roles, the types of work they do, the skills required, and some actionable advice for landing the role of your choosing. What You'll Learn: Why Chris started Maven Analytics, and what the early days were like How the company has evolved over time What's coming up next for the company and for our learners   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   About our guests: Chris Bruehl is a Python expert, certified Statistical Business Analyst, and seasoned Data Scientist, having held senior-level roles at large insurance firms and financial service companies. He earned a Masters in Analytics at NC State's Institute for Advanced Analytics, where he founded the IAA Follow Chris on LinkedIn   Alice Zhao is a seasoned data scientist and author of the book, SQL Pocket Guide, 4th Edition (O'Reilly). She has taught numerous courses in Python, SQL, and R as a data science instructor at Maven Analytics and Metis, and as a co-founder of Best Fit Analytics. Follow Alice on LinkedIn

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We talked about:

00:00 DataTalks.Club intro 01:56 Using data to create livable cities 02:52 Rachel's career journey: from geography to urban data science 04:20 What does a transport scientist do? 05:34 Short-term and long-term transportation planning 06:14 Data sources for transportation planning in Singapore 08:38 Rachel's motivation for combining geography and data science 10:19 Urban design and its connection to geography 13:12 Defining a livable city 15:30 Livability of Singapore and urban planning 18:24 Role of data science in urban and transportation planning 20:31 Predicting travel patterns for future transportation needs 22:02 Data collection and processing in transportation systems 24:02 Use of real-time data for traffic management 27:06 Incorporating generative AI into data engineering 30:09 Data analysis for transportation policies 33:19 Technologies used in text-to-SQL projects 36:12 Handling large datasets and transportation data in Singapore 42:17 Generative AI applications beyond text-to-SQL 45:26 Publishing public data and maintaining privacy 45:52 Recommended datasets and projects for data engineering beginners 49:16 Recommended resources for learning urban data science

About the speaker:

Rachel is an urban data scientist dedicated to creating liveable cities through the innovative use of data. With a background in geography, and a masters in urban data science, she blends qualitative and quantitative analysis to tackle urban challenges. Her aim is to integrate data driven techniques with urban design to foster sustainable and equitable urban environments. 

Links: - https://datamall.lta.gov.sg/content/datamall/en/dynamic-data.html

00:00 DataTalks.Club intro 01:56 Using data to create livable cities 02:52 Rachel's career journey: from geography to urban data science 04:20 What does a transport scientist do? 05:34 Short-term and long-term transportation planning 06:14 Data sources for transportation planning in Singapore 08:38 Rachel's motivation for combining geography and data science 10:19 Urban design and its connection to geography 13:12 Defining a livable city 15:30 Livability of Singapore and urban planning 18:24 Role of data science in urban and transportation planning 20:31 Predicting travel patterns for future transportation needs 22:02 Data collection and processing in transportation systems 24:02 Use of real-time data for traffic management 27:06 Incorporating generative AI into data engineering 30:09 Data analysis for transportation policies 33:19 Technologies used in text-to-SQL projects 36:12 Handling large datasets and transportation data in Singapore 42:17 Generative AI applications beyond text-to-SQL 45:26 Publishing public data and maintaining privacy 45:52 Recommended datasets and projects for data engineering beginners 49:16 Recommended resources for learning urban data science

Join our slack: https: //datatalks.club/slack.html