Apache Kafka

The Fellowship of the Star Schema: Transforming OLTP Data for Power BI One does not simply build reports on OLTP data. Join us on an epic journey from the depths of raw, normalized tables to the shining halls of a well-modeled star schema fit for Power BI greatness. We will demystify the differences between OLTP and OLAP, walk through star schema vs snowflake (and why Power BI has a clear favorite), and show you the compression differences between normalized and columnar storage that will make you never look at an OLTP model the same way again. We will cover the different types of dimensions, when to use them, and how to handle Slowly Changing Dimensions without losing your mind. You will leave knowing exactly how to identify a bad model, how to convert OLTP data into a clean star schema, and how to forge relationships that rule them all. Whether you are a data wizard, a curious hobbit, or somewhere in between, your models will never be the same.

Pay attention! We’re delaying a week for those of you who may be on Spring break and/or celebrating the holiday. Ok, no pancakes, but waffles-a-plenty. Join the local UX and Digital Design community for a casual monthly breakfast. Look for us upstairs!

Salsamante Dance Academy will be at Swerve Every Tuesday Night to share the Rhythm & Energy of Bachata & Salsa. These are Beginner Level lessons to get you comfortable and understand the two dances. Spread the Good News to all. Swerve Dance & Fitness Complex 640 Lakeview Plaza Blvd A, Worthington, OH 43085 Bachata 7pm-8pm Salsa 8pm-9pm $15 - One Lesson $20 - Both Lessons

The global Azure community is coming together again, and Columbus is officially on the map. View the session lineup and speakers at [Global Azure Columbus 2026](https://coazure.github.io/cbus-global-azure-2026/) On **Saturday, April 18, 2026**, the Azure Columbus Meetup, DevOps Meetup, and Code and Coffee Meetup are hosting our local edition of Global Azure 2026. This is a free, community-driven event packed with learning, networking, and all things Microsoft Azure. Whether you’re building modern cloud-native apps, experimenting with AI agents, deploying containers, automating infrastructure, or just beginning your Azure journey, this event is for you! **What to Expect** * Engaging technical sessions * Real-world Azure architecture & cloud-native patterns * AI, agents, automation, and modern DevOps * Food and drinks (because learning burns calories) * Time to connect with fellow engineers, architects, and cloud enthusiasts **Who Should Attend?** * Software engineers (any language, any stack) * Cloud architects * DevOps engineers * Data professionals * AI explorers * Platform builders * Anyone who loves solving hard problems with great tools If you build, deploy, automate, scale, monitor, or optimize in Azure, you’ll feel right at home. **Why Global Azure?** Global Azure is a worldwide community event where Azure user groups host learning sessions on the same day across the globe. It’s grassroots. It’s technical. It’s practical. And it’s powered by people who genuinely love sharing what they’ve learned. And yes, it’s free to attend!

This presentation delves into the potential of integrating LLMs with Apache Spark and Apache Iceberg as part of a Big Data to AI foundational architecture. In this session we’ll explore the potential of combining Iceberg, Spark and LLMs to give you a real world AI architecture that uses your data. We'll build an AI application that allows users to perform data queries and extract insights from massive datasets using natural language. We'll start with understanding the structure and architecture of a large dataset. Then we'll look at options for querying the dataset using Apache Spark and Trino. Finally, we'll use an LLM to query the dataset using natural language. We'll also look at other uses of LLMs as part of an overall solution, and explore the differences between different LLMs. We’ll also discuss where event streaming (Kafka and Flink) fit into this architecture. The design of this architecture is meant to be flexible and give your dev team the ability to choose different technologies for the processing and querying. I’ll leave you with a CONCRETE example that you can run on your laptop and explore the possibilities. Again, this will be an example of a real-world application; the dataset used will be for home sales data for the last 15 years. We will use these technologies: * Apache Iceberg * Apache Spark * Spring AI * Ollama * Various LLMs

Central Ohio Radio Enthusiasts—CORE—is an informal community for anyone enthusiastic or curious about radio—whether you're new to radio and want to learn or you've been tinkering for years and want to share. Ham radio operators, GMRS users, Meshtastic fans, software-defined radio nerds, makers, and technical and non-technical folks are all welcome. No experience required or expected. This month we have **WiFi HaLow: Introduction and Practical Use** with **Alex Barbur**. Details are are [core.radio](https://core.radio).