"Extract, transform, load" (ETL) is at the center of every application of data, from business intelligence to AI. Constant shifts in the data landscape—including the implementations of lakehouse architectures and the importance of high-scale real-time data—mean that today's data practitioners must approach ETL a bit differently. This updated technical guide offers data engineers, engineering managers, and architects an overview of the modern ETL process, along with the challenges you're likely to face and the strategic patterns that will help you overcome them. You'll come away equipped to make informed decisions when implementing ETL and confident about choosing the technology stack that will help you succeed. Discover what ETL looks like in the new world of data lakehouses Learn how to deal with real-time data Explore low-code ETL tools Understand how to best achieve scale, performance, and observability

Teams in our organisations have both data and business requirements… all we have to do is train people how to use Power BI Desktop/Power Query and they can rapidly author their own MIBI reporting. By upskilling your existing staff your organisation will gain ownership of the outputs and reduce the need for contractors.

In this interactive session we will structure a 2-day Power BI training plan outline, giving all attendees an effective framework to use to deliver to their colleagues.

Migrating your BI platform sounds daunting — especially when you’re staring down hundreds of dashboards, years of legacy content, and a hard deadline. At Game Lounge, we made the leap from Looker to Omni, migrating over 800 dashboards in under three months — without disrupting the business.

In this session, we’ll walk through the practical playbook behind our successful migration: how we scoped the project, prioritised what mattered most, and moved quickly without compromising quality. We’ll share how we phased the migration, reduced dashboard sprawl by over 80%, and leaned on Omni’s AI-assisted features to accelerate setup and streamline cleanup.

We’ll also touch on how we kept quality high post-migration — introducing initiatives like dashboard verification to ensure lasting data trust. And we’ll share what happened next, with over 140 employees now using data to inform decisions every day.

Whether you’re planninga migration or trying to make sense of legacy BI sprawl, this session offers honest lessons, practical frameworks, and time-saving tips to help your team move fast and build smarter.

Analytical Data Product success is traditionally measured with classic reliability metrics. If we were ambitious, we might track user engagement by dashboard views or self-serve activity; they are blunt, woolly indicators at best. The real goal was always to enable better decisions, but we often struggle to measure whether our data products actually help. Conversational BI changes this equation. Now we can see the exact questions users are asking, what follow-ups they need, and where the data model delights or frustrates them. This creates a richer feedback loop than ever before, but it also puts our data model front and centre, exposed directly to business users in a way that makes design quality impossible to hide.

This session will recap the foundations of good data product design, then dive into what conversational BI means for analytics teams. How do we design models that give the best foundation? How can we capture and interpret this new stream of usage feedback? What does success look like? We'll answer all of these questions and more.

Data’s not what it was. Analytics is shifting fast - so how should we rethink data product design before we’re left in the dust?

Discover examples of a semantic layer built with data products that power both BI and AI.

AI innovation shouldn’t be gated by pipeline delays or data migrations. This session shows how federated data products deliver instant, trusted access—fueling chatbots, agents, and multi-agent workflows that solve real business problems.

We’ll walk through examples of a semantic layer built with data products that power both BI and AI. You’ll see how data products ensure more accurate AI results, simplify governance, and support experimentation with any LLM or agent framework.

Real-world use cases will include:

* A 1-day chatbot business project for answering questions with governed data

* An autonomous agent driving decisions from live sources

* A multi-agent workflow delivering dynamic, real-time insights

Leave with a practical blueprint to accelerate AI—no warehouse rewrites, no delays, just results.

Business challenges that were once sporadic are now persistent and widespread—impacting everyone across the organization, from business users and analysts to data engineers and scientists.

To keep pace, BI platforms have steadily evolved, embracing technologies that empower every user to tackle growing data complexity with confidence.

Now, with sophisticated Gen AI and Agentic AI capabilities built into these platforms, we’re stepping into a new era of analytics—one that redefines what data democratization means for modern businesses.

Join us for an exclusive session where we’ll explore how the latest innovations in Gen AI are reshaping the BI landscape and unlocking powerful, actionable insights for every user.

In this session, you’ll learn:

- What defines a truly Gen AI-powered BI platform

- How businesses can empower every user with cutting-edge Gen AI

- How Agentic AI is shaping BI

- Live demos showcasing Gen AI and Agentic AI capabilities in BI

- Discover how a Gen BI platform can drive smarter decisions, boost productivity, and deliver transformative business outcomes.

How do you enable thousands of users to confidently work with vast amounts of data? For PlayStation, the answer lay in a hub and spoke model and an approach that combined governance with community.  

In this session, Oleksii Zakrevskyi, PlayStation’s Business Intelligence Tech Lead, will share how they built their hub and spoke model that ensures secure access, while fostering adoption through collaboration and shared standards. The presentation will also explore the user experience innovations—from custom home pages to consistent design—that make data rapidly discoverable and trusted. A fireside chat and Q&A will follow.

Discussion on lessons learned from Fabric PoCs, including Fabric new features and migrating Power BI workloads from PBI Premium to Fabric.

EBMT, one of the biggest medical registries in Europe, has rebuilt its core data system from scratch, after 20 years of service, to keep up with growing data needs, modern technologies, and the evolving needs of researchers in blood and marrow transplantation. The new AWS-based system supports data collection and analysis at scale, using cloud infrastructure and business intelligence tools to improve data quality and data usability across EBMT’s network.

Hoe zorg je ervoor dat je data sneller, betrouwbaarder en met minder handmatige werkzaamheden beschikbaar is voor analyse? Anne Marthe den Hartog (Aviation & Business Intelligence specialist) en Wim Fieret (Data & Analytics specialist) van Rotterdam The Hague Airport vertellen hoe zij de overstap maakten van hun oude manier van datavoorbereiding naar een low-code datafundament met TimeXtender. Tijdens deze sessie delen ze hun ervaringen en praktische voordelen die deze nieuwe werkwijze oplevert.

In deze klantcase licht Victor Oudsen, IT Lead Business Intelligence bij Normec toe hoe de transitie naar Microsoft Fabric is aangepakt – van de gekozen architectuur tot de eerste inzichten.

Business challenges that were once sporadic are now persistent and widespread—impacting everyone from business users and analysts to data engineers and scientists. Learn how the latest innovations in Gen AI are reshaping the BI landscape and unlocking actionable insights for every user. Here's what we'll cover: What defines a truly Gen AI-powered BI platform How businesses can empower every user with Gen AI How Agentic AI is shaping BI Live demos showcasing Gen AI and Agentic AI capabilities in BI

Tristan talks with Mikkel Dengsøe, co-founder at SYNQ, to break down what agentic coding looks like in analytics engineering. Mikkel walks through a hands-on project using Cursor, the dbt MCP server, Omni's AI assistant, and Snowflake. They cover where agents shine (staging, unit tests, lineage-aware checks), where they're risky (BI chat for non-experts), and how observability is shifting from dashboards to root-cause explanations. 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.

Here are 5 exciting and unique data analyst projects that will build your skills and impress hiring managers! These range from beginner to advanced and are designed to enhance your data storytelling abilities. ✨ Try Julius today at https://landadatajob.com/Julius-YT Where I Go To Find Datasets (as a data analyst) 👉 https://youtu.be/DHfuvMyBofE?si=ABsdUfzgG7Nsbl89 💌 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 00:24 - Project 1: Stock Price Analysis 03:46 - Project 2: Real Estate Data Analysis (SQL) 07:52 - Project 3: Personal Finance Dashboard (Tableau or Power BI) 11:20 - Project 4: Pokemon Analysis (Python) 14:16 - Project 5: Football Data Analysis (any tool)

🔗 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!

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