Together with Global AI Berlin

Hey guys,

it's that time again. After last year's successful Holy Tech Night, here we go again. Holy Tech Night organized by Janek. Three speakers will once again provide us with nerdy stuff for the evening, covering three different topics from the Microsoft world. During the breaks and afterwards, mulled wine and gingerbread will be available to see out the year in style.

Anyone who wants to is welcome to come in a suitable outfit - some of you still have an ugly sweater at home. 🫣😆

Here ist the agenda:

18:00 doors open 18:15 first talk 19:00 short break 19:05 second talk 19:50 short break 20:00 third talk 20:45 networking

Our speakers and its topics this year:

Michael Greth Psst ... Private Local AI – Turn your Mac into a Private AI Power House

As the year winds down and things get a little quieter, it’s the perfect moment to take a fresh look at what my computer (MacMini M4) can already do. In this session, you’ll discover how to turn it into a private AI powerhouse — without cloud dependencies, subscriptions, or data leaving your device. We’ll explore Small Language Models, LM Studio, MacWhisper, and AnythingLLM, and walk through practical examples for local transcription, document analysis, and fast on-device reasoning. By the end, you’ll know exactly what to play with between Christmas and New Year.

Thomas Stensitzki Holy Hybrid: The Last Jedi of the Exchange World

Exchange Hybrid is more than a temporary solution. It is the strategic bridge between on-premises and the cloud. In this session, you’ll learn why hybrid setups remain relevant in 2025, the common pitfalls to avoid, and how to implement best practices for a smooth migration. We will dive into authentication, connectivity, and the future of Exchange in a cloud-first world. Perfect for IT pros who want to master the middle ground without getting lost in complexity.

Markus Raatz Fabric IQ

With the new Fabric IQ, Microsoft is taking a big leap forward: rather than IT specialists, it is the business users who define and describe how the business works using an ontology, via entities with properties and relationships between them. They then explain to Microsoft Fabric where the relevant data can be found, and a data agent can then be used to query all aspects of the business and analyze them. And because it knows the entire business with its rules and not just one department, it can automatically make decisions that are almost as good as those made by its human colleagues. Not quite clear? No matter, this presentation has some good examples.

Nora Szentivanyi and Michael Hanson discuss the latest global CPI reports and the implications for central banks. We also delve deeper into the topic of tariff-induced inflation in the US. The global top-down message remains one of continued sticky inflation around 3%. Along with the trimming of downside growth risks, this has unsurprisingly prompted central banks to turn less dovish. While US core inflation has risen less than expected at the outset of the trade war, it is running well above target and we still anticipate tariff-related pressures will push it higher, with the likely peak now in 1Q26.  Outside the US, core inflation has moderated somewhat as goods inflation is not seeing the same tariff-induced bounce. However, core services inflation has yet to fully normalize, and volatile items add to the sticky core picture.

Speakers: Nora Szentivanyi, Senior Global Economist  Michael Hanson, Senior US and Canada Economist

This podcast was recorded on October 4, 2025. 

This communication is provided for information purposes only. Institutional clients can view the related report at https://www.jpmm.com/research/content/GPS-5113765-0; https://www.jpmm.com/research/content/GPS-5094754-0; and https://www.jpmm.com/research/content/GPS-5110036-0 for more information; please visit www.jpmm.com/research/disclosures for important disclosures. © 2025 JPMorgan Chase & Co. All rights reserved.

From spreadsheets to strategy: what does data look like from the CEO's chair? For this episode, we sat down with Anna Lee, CEO of Flybuys and former CFO/COO of THE ICONIC, to get her view on data-led leadership and what great looks like in data and analytics. Discover how Anna's journey from finance to the corner office has shaped her approach to leveraging evidence for strategic decision-making. From productive curiosity, to informed pragmatism, and how data teams can build trust with leadership, this is a candid conversation about analytics from the top down. Whether you're embedded in a squad or building the next big data platform, this one's for anyone who's ever wondered what it takes to truly influence the C-suite! This episode's Measurement Bite from show sponsor Recast is an overview of the fundamental problem of causal inference from Michael Kaminsky! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Hello and welcome to Global AI Bootcamp 2025 Digital

FOR COMMUNITY BY THE COMMUNITY

Event link via MS Teams

We understand the value of networking, sharing knowledge, and mutual inspiration. Our platform offers a unique opportunity to connect with like-minded individuals, exchange ideas, and learn from each other.

We invite you to join our community and participate in this enriching experience. Let’s grow, learn, and succeed together.

The Global AI Bootcamp is a free one-day event hosted by local communities worldwide who are passionate about intelligence in Microsoft Azure. The event is a perfect mix of quality content, great presentations and hands-on learning with like-minded people in your community.

4 hours: 14.00 -18.00 CET, online on Microsoft Teams 4 Tracks: AI, Azure, Copilots and Microsoft 365 Participation is free of charge.

Global AI Chapter Berlin (Zaid Zaim) Global AI Chapter Bochum (Thorsten Pickhan, Adrian Ritter) Global AI Chapter Karlsruhe (Alexander Wachtel) Global AI Chapter Köln (Raphael Köllner) Global AI Chapter München (Michael Plettner, Ralf Richter) Global AI Chapter Nürnberg (Dennis Weber) Global AI Chapter Zurich (Jose Luis Latorre Millas)

Event Tracks: Main Track

• 14.00 Welcome by All Global AI Chapters DACH
• 14.10 Keynote by Femke
• 17.30 Endnote

14.35 – 17.30 AI Track Azure Track Copilots Track Microsoft 365 Track

Agenda: 14.00 - 14.10 Welcome 14.10 - 14.30 Keynote Thriving in Tech During the AI Revolution – Career Growth & Personal Branding Femke Cornelissen, Technical Evangelist at Wortell & Microsoft MVP 14.35 - 15.05 (AI Track) Semantic All-The-Things: Why Embedding Models Might Be More Important Than Language Models Christian Weyer, Microsoft MVP & RD, CTO @ Thinktecture AG (Azure Track) Deploying a Chatbot via Azure AI and Slack Nicholas Chang, Microsoft Azure MVP & Senior Platform Engineer@ Kainos (Copilots Track) Copilot YES but which one, when Michael Plettner, Microsoft MVP & CEO in2success (Microsoft 365 Track) Responsible AI at Microsoft and the AI Act Raphael Koellner, Microsoft RD, MVP Office Apps and Services 15.10 - 15.40 (AI Track) How to enhance your own AI services using Semantic Kernel Håkan Silfvernagel, AI Evangelist, Microsoft AI MVP (Azure Track) Unlock the Power of AI: From Play to Productivity Ralf Richter, Director Consulting Expert @CGI, Azure & AI MVP (Copilots Track) How to master Copilot for Microsoft 365 Giuliano De Luca, Solutions Architect @ BMW & Microsoft MVP Federico Porceddu, M365 MVP & Modern Workplace Solution Architect (Microsoft 365 Track) Data Security Posture Management for AI Uros Babic, Security Architect @ Crayon, Microsoft Security MVP, MCT 15.45 - 15.15 (AI Track) Attacking LLM Detectors with Homoglyph-Based Attacks Aldan Creo, Technology Research Specialist @ Accenture Labs (Azure Track) Building a ChatOps Workflow with GPT Models and Azure DevOps Estelle Auberix, CEO @IOKELA, Co-founder @Cloudhersity, Microsoft RD, MCT (Copilots Track) Unlocking the Power of Copilot Agents: Creation, Features, and Licensing Tanja Wiehoff, M365 Solution Consultant, Copilot Prompster (Microsoft 365 Track) Data chaos reloaded: How a lack of data governance is slowing down Copilot Fabio Bonolo, Microsoft MVP, Teamleader Productivity M365 & Power Platform @ redIT 16.20 - 16.50 (AI Track) AI Agents in Action Dr. Alexander Wachtel, Microsoft AI MVP, MCT & CEO @ ESC Deutschland (Azure Track) Securing Azure OpenAI and Azure AI Services: Best Practices for the field Tiago Costa, Cloud Architect and Advisor, MCT (Copilots Track) Extend Teams using Microsoft Copilot Studio Marcin Siewnicki, Microsoft 365 Consultant and Architect (Microsoft 365 Track) Empower Microsoft Fabric solutions using Generative AI on top of data in Fabric Mihail Mateev, Senior Solution Architect @ EPAM Systems 16.55 - 17.25 (AI Track) Agents, Semantic Kernel & Azure AI Foundry Jose Luis Latorre Millas, Microsoft AI MVP, Software Developer @ Swiss Life (Azure Track) Vision to Visualisation: Using GitHub Copilot for Azure and Diagrams Marcel Lupo, Microsoft MVP DevOps + Azure, Cloud Solutions & DevOps Architect (Copilots Track) High-end agents with Copilot Studio and Azure OpenAI Sabrina Göttlinger, Team Lead AI Solutions @Skaylink & Microsoft MVP (Microsoft 365 Track) Discover Planner Copilot and Planner Premium Daniel Rohregger, Cloud Architect @ Glueckkanja AG 17.30 - 18.00 Endnote Patrick Chanezon, VP Developer Relations @ Microsoft

How can businesses align AI with their values? How does decentralized data impact industries from healthcare to autonomous driving? In this episode of Data Unchained we sit down with Michael Hemenway, a Data Science Consultant, to discuss AI ethics, governance, and the future of responsible technology adoption.

AI #EthicalAI #DataScience #MachineLearning #ArtificialIntelligence #DataUnchained #TechPodcast #CIO #CTO #DecentralizedData #Governance #DeepLearning #BusinessStrategy #FutureTech

Cyberpunk by jiglr | https://soundcloud.com/jiglrmusic Music promoted by https://www.free-stock-music.com Creative Commons Attribution 3.0 Unported License https://creativecommons.org/licenses/by/3.0/deed.en_US Hosted on Acast. See acast.com/privacy for more information.

It's been said that, in this world, nothing is certain except death and taxes, so why is it so hard to communicate uncertainty to stakeholders when delivering an analysis? Many stakeholders think an analysis is intended to deliver an absolute truth; that if they have just enough data, a smart analyst, and some fancy techniques, that the decision they should make will emerge! In this episode, Tim, Moe, and Val sat down with Michael Kaminsky, co-founder of Recast, to discuss strategies such as scenario planning and triangulation to help navigate these tricky conversations. Get comfortable with communicating the strengths and drawbacks of your different methodological approaches to empower decision making from your stakeholders! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

This event will illuminate how developers can leverage Testcontainers to create replicable testing environments, ensuring that Neo4j-based applications run flawlessly in any setup.

We will use hands-on examples and share insights and best practices for setting up, configuring, and tearing down Neo4j instances for testing within containerised environments.

Guests: Oleg Šelajev, Atomicjar & Michael Simons, Neo4j

This event will illuminate how developers can leverage Testcontainers to create replicable testing environments, ensuring that Neo4j-based applications run flawlessly in any setup.

We will use hands-on examples and share insights and best practices for setting up, configuring, and tearing down Neo4j instances for testing within containerised environments.

Guests: Oleg Šelajev, Atomicjar & Michael Simons, Neo4j

This event will illuminate how developers can leverage Testcontainers to create replicable testing environments, ensuring that Neo4j-based applications run flawlessly in any setup.

We will use hands-on examples and share insights and best practices for setting up, configuring, and tearing down Neo4j instances for testing within containerised environments.

Guests: Oleg Šelajev, Atomicjar & Michael Simons, Neo4j

This event will illuminate how developers can leverage Testcontainers to create replicable testing environments, ensuring that Neo4j-based applications run flawlessly in any setup.

We will use hands-on examples and share insights and best practices for setting up, configuring, and tearing down Neo4j instances for testing within containerised environments.

Guests: Oleg Šelajev, Atomicjar & Michael Simons, Neo4j

Summary The most important gauge of success for a data platform is the level of trust in the accuracy of the information that it provides. In order to build and maintain that trust it is necessary to invest in defining, monitoring, and enforcing data quality metrics. In this episode Michael Harper advocates for proactive data quality and starting with the source, rather than being reactive and having to work backwards from when a problem is found.

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 managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! Atlan is a collaborative workspace for data-driven teams, like Github for engineering or Figma for design teams. By acting as a virtual hub for data assets ranging from tables and dashboards to SQL snippets & code, Atlan enables teams to create a single source of truth for all their data assets, and collaborate across the modern data stack through deep integrations with tools like Snowflake, Slack, Looker and more. Go to dataengineeringpodcast.com/atlan today and sign up for a free trial. If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code. Monitoring data quality, tracing incidents, and testing changes can be daunting and often takes hours to days. Datafold helps Data teams gain visibility and confidence in the quality of their analytical data through data profiling, column-level lineage and intelligent anomaly detection. Datafold also helps automate regression testing of ETL code with its Data Diff feature that instantly shows how a change in ETL or BI code affects the produced data, both on a statistical level and down to individual rows and values. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Go to dataengineeringpodcast.com/datafold today to start a 30-day trial of Datafold. Your host is Tobias Macey and today I’m interviewing Michael Harper about definitions of data quality and where to define and enforce it in the data platform

Interview

Introduction How did you get involved in the area of data management? What is your definition for the term "data quality" and what are the implied goals that it embodies?

What are some ways that different stakeholders and participants in the data lifecycle might disagree about the definitions and manifestations of data quality?

The market for "data quality tools" has been growing and gaining attention recently. How would you categorize the different approaches taken by open source and commercial options in the ecosystem?

What are the tradeoffs that you see in each approach? (e.g. data warehouse as a chokepoint vs quality checks on extract)

What are the difficulties that engineers and stakeholders encounter when identifying and defining information that is necessary to identify issues in their workflows? Can you describe some examples of adding data quality checks to the beginning stages of a data workflow and the kinds of issues that can be identified?

What are some ways that quality and observability metrics can be aggregated across multiple pipeline stages to identify more complex issues?

In application observa

Highlights  “Scooter Braun's Ithaca Holdings Acquires Scott Borchetta's Big Machine Label Group” is what Sunday’s official press release reads, we’ll take a look at a sample of Swift’s data while on Big Machine and on Republic RecordsMission   Good morning, it’s Jason here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.DateThis is your Data Dump for Tuesday, July 2nd, 2019.Taylor Swift: Before and After Big MachineThe music business’ latest media frenzy revolves around a music mogul acquiring a top music star’s catalog.This is reminiscent of how in 1985, the late King of Pop, Michael Jackson, acquired the Beatles’ catalog of song copyrights, after receiving advice from Paul McCartney himself that music publishing was a great business to get into.Current music executive Scooter Braun and his Ithaca Holdings media company purchased Nashville-based Big Machine Label Group, Taylor Swift’s former label,  for lots of money. This was announced over the weekend.Big Machine’s assets include Swift’s catalog up through 2017’s “Reputation”.She signed to UMG’s Republic Records in 2018, and now owns her own future masters starting with the album “Lover”.While we don’t have data on the controversy, we can look at two tracks: one from Swift’s Big Machine era, and one from her Republic Records era.The former is “Look What You Made Me Do” from 2017’s “Reputation” album while the latter is the first single from the 2019 album “Lover,” “You Need to Calm Down”.Big Machine-owned “Look What You Made Me Do”...was released almost two years ago in August 2017.Currently at a 75 out of 100 Spotify Popularity Index (or SPI), it was at 91 SPI in Nov 2018.The track is on 1.6K Spotify playlists, 17 of them editorial including the This Is: Taylor Swift playlist.......while it also has a current spot on 77 Apple Music playlists and 27 Amazon playlists, all editorial for the latter case.In her Republic-era, “You Need to Calm Down”...was released just two weeks ago in June 2019.Currently at 92 SPI, it’s on less total Spotify playlists at 1.1K, but is on more editorial at 94, which makes sense since it’s relatively a brand new release.It’s on almost three times as many Apple Music playlists at 202, and 3.5x as many Amazon playlists at 98.So is it fair to say that the Republic era is “better”? Not necessarily- again, it’s just a newer track and her Big Machine track was in the middle of her 2014-2018 Spotify absence, limiting a big part of her data profile.But what this kind of side-by-side track comparison CAN do is help you evaluate how well tracks do under different promotional strategies, label teams or simply with different types of music.Hope it’s useful.Outro That’s it for your Daily Data Dump for Tuesday, July 2nd, 2019. This is Jason from Chartmetric.Free accounts are at chartmetric.comAnd article links and show notes are at: podcast.chartmetric.comHappy Tuesday, and we’ll see you tomorrow!