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Unlock the Power of Data with CrateDB & AWS**: A Hands-On Workshop.**

Join us for a dynamic, hands-on morning that will transform the way you think about data analytics and AI. Designed for data-driven professionals across sectors, this event delivers hands-on sessions, real-world AI applications, and the latest in scalable analytics. Secure your spot and discover how CrateDB and AWS are shaping the future of data.

We’ll dive into the world of multi-model databases and explore how time-series data can be enriched with geospatial and vector data. From there, we will build an AI agent that enables interpreting data using natural language with the help of an LLM.

Hands-On Workshops with CrateDB’s Solutions Engineers

Get ready to work directly with CrateDB’s solutions engineers as they guide you through two engaging hands-on sessions, using Jupyter notebooks. Everything runs smoothly in the cloud, so you can focus on learning and experimenting.

What to Bring

Bring your laptop and your curiosity! No software installation is required as all labs run in the cloud. Basic SQL and Python knowledge is recommended but not essential.

Register Today – Don’t Miss Out!

Fill in the registration form to save your seat for this educational morning. After submission, you will receive an email within 48/72 hours to confirm your registration. This session is also a great opportunity to participate in deep technical discussions and exchange ideas with your peers. Don’t miss this chance to elevate your technical skills and discover how modern data technologies can fuel innovation!

About CrateDB

CrateDB is a distributed database that empowers organizations with a Unified Data Layer to process, analyze, and act on high-velocity data at scale. Designed for speed, scalability, and flexibility, CrateDB seamlessly integrates real-time analytics, full-text and vector search, and AI-driven capabilities into a single, cohesive platform.

CrateDB Cloud on AWS offers a seamless and scalable SQL database solution for managing all types of data for advanced analytics and machine learning applications. Available on AWS, CrateDB Cloud enables the deployment of modern, scalable applications, ensuring compliance with strict security standards.

About AWS

Amazon Web Services (AWS) is a widely adopted cloud platform, offering +200 fully featured services from data centers globally. AWS empowers organizations of all sizes - from startups to enterprises, government agencies, and nonprofits - to innovate, scale, and transform their operations with secure, reliable, and cost-effective cloud infrastructure. AWS enables customers to build, deploy, and manage applications with unmatched flexibility and scalability, helping them accelerate growth and drive meaningful impact across industries.

Venue

Amazon Web Services Munich Office Oskar-von-Miller-Ring 20 80333 München Germany Google maps

Venue: Carnival House, 100 Harbour Parade, Southampton, SO15 1ST 📢 Want to speak 📢: submit your talk proposal

Main Talks 1️⃣ Visual Place Recognition - Emily Miller Visual Place Recognition (VPR) is a critical task in robotics and autonomous systems, enabling machines to recognise and localise themselves within an environment using visual cues. This talk will dive into the key concepts of VPR, with a focus on Python-based tools and libraries that simplify the implementation of VPR algorithms. We'll explore feature extraction techniques, the role of deep learning in advancing VPR, and practical applications for real-world problems. Whether you're building autonomous drones or smart city solutions, this talk will provide insights on using Python to develop robust and scalable VPR systems.

2️⃣ Faster Models, Faster Answers: Discover Emulation for Your Workflow - Austen Wallis AI this and AI that, the world in the past couple of years has become overrun with news of Generative AI and the ever-improving odds of a takeover from our new robot overlord, ChatGPT. However, have you ever heard about Generative Modelling? This research field is no longer just about creating pretty pictures and making funky tunes about your favourite branded baked beans. No, step with me into the world of Emulation! We’ll probe how simple generative deep-learning models can improve complex physics simulations to not only be rapid but quick as a flash. So, fasten your seat belts as I take you on an ultra-fast whistle-stop tour exploring the universe of surrogate modelling, neural networks and the latent space. As I showcase the raw power of emulators, we’ll uncover how faster models unlock new answers (and questions) in both Astrophysics and fusion energy. Also, we’ll examine introductory examples of how you can build your own emulator from scratch.

For an evening event, you don’t want to miss, I look forward to seeing you there ... and bring a fire extinguisher; my GPU will be on fire 🔥!

Lightning Talks ⚡ ⚡1️⃣ TBD ⚡2️⃣ TBD

Please note:

1. 🚨🚨🚨A valid photo ID is required by building security. You MUST use your initial/first name and surname on your meetup profile, otherwise, you will NOT make it on the guest list! 🚨🚨🚨
2. This event follows the NumFOCUS Code of Conduct, please familiarise yourself with it before the event.

If your RSVP status says "You're going" you will be able to get in. No further confirmation required. You will NOT need to show your RSVP confirmation when signing in. If you can no longer make it, please unRSVP as soon as you know so we can assign your place to someone on the waiting list.

*** Code of Conduct: This event follows the NumFOCUS Code of Conduct, please familiarise yourself with it before the event. Please get in touch with the organisers with any questions or concerns regarding the Code of Conduct. *** There will be pizza & drinks, generously provided by our host, Carnival UK. ***

Logistics Doors open at 6.30 pm, talks start at 7 pm. For those who wish to continue networking and chatting we will move to a nearby pub/bar for drinks from 9 pm.

Please unRSVP in good time if you realise you can't make it. We're limited by building security on the number of attendees, so please free up your place for your fellow community members!

Follow @pydatasoton (https://twitter.com/pydatasoton) for updates and early announcements. We are also on Instagram/Threads as @pydatasoton, and find us on LinkedIn.

We are in a modern world now, especially in the DBA world. There are so many tools out there that have a GUI attached to them and that is fantastic to have such choices. In the new world, you want to get more done than ever before in the same amount of time. This session is NOT about replacing every DBA tool with PowerShell, it is ALL about adding PowerShell to your vast array of tools. I will show you how easy it is to get more done without clicking around a GUI and you'll exactly what you without clicking on tabs. You can even make changes across databases and instances. Join me in a demo filled session to show you how much you really can get out of adding PowerShell to your list of tools and you will never regret it. So many tools and not enough time, but you don't have to write any PowerShell to get where you want to go, and you'll get there faster.

Advances in LLM technology and the semantic layer have made AI-powered data analytics easy. Nothing special. Par for the course.

Wait, you haven't seen yet? Don't worry, we'll show you. But I gotta warn you, it's pretty boring stuff. You just ask for whatever data you want, and then the computer gets it for you. Yes, seriously!

So what is still impressive in October 2023? Well, good old fashioned human ingenuity and improvisational skill. Computers may have gotten pretty good at crunching the numbers, but you still can't replace good old fashioned meat and bone when it comes time to present those numbers to the big boss.

In this session, Izzy Miller and Matt David put that to the test with a live game of Dashboard Karaoke— with an AI twist. Random audience members take turns using Hex's Magic AI to generate entire analytical reports on datasets of their choosing. Then, our handpicked data practitioners have to improvise a compelling presentation of the results on the spot, explaining the intricacies and trends of data they've never seen. And of course, there will be plenty of time for audience questions ;)

Speakers: Izzy Miller, Developer Advocate, Hex; Matt David, Product Marketing Lead, Hex

Register for Coalesce at https://coalesce.getdbt.com

Today I’m chatting with returning guest Tom Davenport, who is a Distinguished Professor at Babson College, a Visiting Professor at Oxford, a Research Fellow at MIT, and a Senior Advisor to Deloitte’s AI practice. He is also the author of three new books (!) on AI and in this episode, we’re discussing the role of product orientation in enterprise data science teams, the skills required, what he’s seeing in the wild in terms of teams adopting this approach, and the value it can create. Back in episode 26, Tom was a guest on my show and he gave the data science/analytics industry an approximate “2 out of 10” rating in terms of its ability to generate value with data. So, naturally, I asked him for an update on that rating, and he kindly obliged. How are you all doing? Listen in to find out!

Highlights / Skip to:

Tom provides an updated rating (between 1-10) as to how well he thinks data science and analytics teams are doing these days at creating economic value (00:44) Why Tom believes that “motivation is not enough for data science work” (03:06) Tom provides his definition of what data products are and some opinions on other industry definitions (04:22) How Tom views the rise of taking a product approach to data roles and why data products must be tied to value (07:55) Tom explains why he feels top down executive support is needed to drive a product orientation (11:51) Brian and Tom discuss how they feel companies should prioritize true data products versus more informal AI efforts (16:26) The trends Tom sees in the companies and teams that are implementing a data product orientation (19:18) Brian and Tom discuss the models they typically see for data teams and their key components (23:18) Tom explains the value and necessity of data product management (34:49) Tom describes his three new books (39:00)

Quotes from Today’s Episode “Data science in general, I think has been focused heavily on motivation to fit lines and curves to data points, and that particular motivation certainly isn’t enough in that even if you create a good model that fits the data, it doesn’t mean at all that is going to produce any economic value.” – Tom Davenport  (03:05)

“If data scientists don’t worry about deployment, then they’re not going to be in their jobs for terribly long because they’re not providing any value to their organizations.” – Tom Davenport (13:25)

“Product also means you got to market this thing if it’s going to be successful. You just can’t assume because it’s a brilliant algorithm with capturing a lot of area under the curve that it’s somehow going to be great for your company.” – Tom Davenport (19:04)

“[PM is] a hard thing, even for people in non-technical roles, because product management has always been a sort of ‘minister without portfolio’ sort of job, and you know, influence without formal authority, where you are responsible for a lot of things happening, but the people don’t report to you, generally.” – Tom Davenport (22:03)

“This collaboration between a human being making a decision and an AI system that might in some cases come up with a different decision but can’t explain itself, that’s a really tough thing to do [well].” – Tom Davenport (28:04)

“This idea that we’re going to use externally-sourced systems for ML is not likely to succeed in many cases because, you know, those vendors didn’t work closely with everybody in your organization” – Tom Davenport (30:21)

“I think it’s unlikely that [organizational gaps] are going to be successfully addressed by merging everybody together in one organization. I think that’s what product managers do is they try to address those gaps in the organization and develop a process that makes coordination at least possible, if not true, all the time.” – Tom Davenport (36:49)

Links Tom’s LinkedIn: https://www.linkedin.com/in/davenporttom/ Tom’s Twitter: https://twitter.com/tdav All-in On AI by Thomas Davenport & Nitin Mittal, 2023 Working With AI by Thomas Davenport & Stephen Miller, 2022 Advanced Introduction to AI in Healthcare by Thomas Davenport, John Glaser, & Elizabeth Gardner, 2022 Competing On Analytics by Thomas Davenport & Jeanne G. Harris, 2007