Tino Tuomi-Nikula

When data agents fail, they often fail silently - giving confident-sounding answers that are wrong, and it can be hard to figure out what caused the failure. "Building and Evaluating Data Agents" is a new short course created with Snowflake and taught by Anupam Datta and Josh Reini. This course teaches you to build data agents with comprehensive evaluation built in. Skills you'll gain: - Build reliable LLM data agents using the Goal-Plan-Action framework and runtime evaluations that catch failures mid-execution - Use OpenTelemetry tracing and evaluation infrastructure to diagnose exactly where agents fail and systematically improve performance - Orchestrate multi-step workflows across web search, SQL, and document retrieval in LangGraph-based agents The result: visibility into every step of your agent's reasoning, so if something breaks, you have a systematic approach to fix it. Sign up to get started: https://lnkd.in/gVwKuCCQ

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𝐃𝐚𝐭𝐚𝐛𝐫𝐢𝐜𝐤𝐬 𝐯𝐬 𝐅𝐚𝐛𝐫𝐢𝐜 – 𝐖𝐡𝐚𝐭 𝐟𝐢𝐭𝐬 𝐲𝐨𝐮𝐫 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐛𝐞𝐬𝐭? (𝐓𝐨𝐦𝐨𝐫𝐫𝐨𝐰, 𝐨𝐧𝐥𝐢𝐧𝐞) If you want to understand how Databricks and Microsoft Fabric are evolving, and what that means in practice for data engineering, governance and reporting, then tune in tomorrow morning! Five months ago, Anders Krohn and I hosted a webinar on the same topic, and the interest much higher than expected. So we’re doing it again, this time with an updated perspective. Both platforms are moving fast, and some of the opinions we had back then might already look a bit different today. 𝐖𝐞’𝐥𝐥 𝐬𝐡𝐚𝐫𝐞 𝐨𝐮𝐫 𝐥𝐚𝐭𝐞𝐬𝐭 𝐭𝐚𝐤𝐞 𝐨𝐧 𝐡𝐨𝐰 𝐭𝐡𝐞 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬 𝐜𝐨𝐦𝐩𝐚𝐫𝐞 𝐢𝐧 terms of: ▪️ Data engineering ▪️ Governance ▪️ Reporting ▪️ How teams are actually using them in real scenarios. This isn’t a feature-by-feature walkthrough. We will focus on understanding how the platforms are developing, where they differ, and where they might overlap. 🗓️ 𝐎𝐧𝐥𝐢𝐧𝐞 𝐭𝐨𝐦𝐨𝐫𝐫𝐨𝐰 🔗 https://lnkd.in/drPYpmrU Evidi Evidi Denmark Torben Nyvang Jakobsen Martin Bundesen Anette Kilebu Brage Rønning Tukkensæter Lars Yngvar Tømmerholt #Databricks #Microsoft #MicrosoftFabric #DatabricksMVP

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Steps here👇the game has completely changed since 2022 - it’s not just leetcode anymore. Here’s what Viktoria Semaan shared that actually worked: ✅ Actually USE the platform (yes, she had to learn Databricks + Spark from scratch) ✅ Nail the coding assignment without ChatGPT crutches ✅ Come with CLEAR impact stories for leadership rounds ✅ Do your homework on every interviewer (LinkedIn stalking is real prep 😅) The technical bar is higher, but the human connection piece is everything. When you can tie your stories to their experience and show genuine interest in their work - that’s when you stand out. 2025 interviews hit different. Preparation is everything 💪 What’s the biggest interview challenge you’re facing right now? Drop it in the comments 👇 #techjobs #interviewtips

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Databricks announces Zerobus - a Kafka-like message bus for writing data directly to your Lakehouse in the Unity Table Format. Zero copy. High throughput. Near real-time latency. Unlike Kafka, this is useful when your only destination is the lake house. I posted a while ago about the idea of open table formats reducing the need for Kafka - if S3 and table formats become the default place to store data, you omit a lot of read fanout jobs that simply copied the data to another system for use. Just store it in one place. Interesting development. It seems like every company is releasing their Kafka-like niched down alternative. (see Cloudflare Pipelines)

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