talk-data.com

Data is your business. Have you unlocked its full potential? If you read nothing else on data strategy, read this book. We've combed through hundreds of Harvard Business Review articles and selected the most important ones to help you maximize your analytics capabilities; harness the power of data, algorithms, and AI; and gain competitive advantage in our hyperconnected world. This book will inspire you to: Reap the rewards of digital transformation Make better data-driven decisions Design breakout products that generate profitable insights Address vulnerabilities to cyberattacks and data breaches Reskill your workforce and build a culture of continuous learning Win with personalized customer experiences at scale This collection of articles includes "What's Your Data Strategy?," by Leandro DalleMule and Thomas H. Davenport; "Democratizing Transformation," by Marco Iansiti and Satya Nadella; "Why Companies Should Consolidate Tech Roles in the C-Suite," by Thomas H. Davenport, John Spens, and Saurabh Gupta; "Developing a Digital Mindset," by Tsedal Neeley and Paul Leonardi; "What Does It Actually Take to Build a Data-Driven Culture?," by Mai B. AlOwaish and Thomas C. Redman; "When Data Creates Competitive Advantage," by Andrei Hagiu and Julian Wright; "Building an Insights Engine," by Frank van den Driest, Stan Sthanunathan, and Keith Weed; "Personalization Done Right," by Mark Abraham and David C. Edelman; "Ensure High-Quality Data Powers Your AI," by Thomas C. Redman; "The Ethics of Managing People's Data," by Michael Segalla and Dominique Rouzies; "Where Data-Driven Decision-Making Can Go Wrong," by Michael Luca and Amy C. Edmondson; "Sizing Up Your Cyberrisks," by Thomas J. Parenty and Jack J. Domet; "A Better Way to Put Your Data to Work," Veeral Desai, Tim Fountaine, and Kayvaun Rowshankish; and "Heavy Machinery Meets AI," by Vijay Govindarajan and Venkat Venkatraman. HBR's 10 Must Reads are definitive collections of classic ideas, practical advice, and essential thinking from the pages of Harvard Business Review. Exploring topics like disruptive innovation, emotional intelligence, and new technology in our ever-evolving world, these books empower any leader to make bold decisions and inspire others.

Join us for an engaging one-hour session designed to unlock the potential of SharePoint in your organisation. Whether you're new to SharePoint or looking to refresh your skills, this overview will provide you with the essential knowledge to harness this powerful platform effectively.

Understand what SharePoint is and its core components. -Explore the benefits for document management and collaboration. -Getting Started with SharePoint:

Navigate the SharePoint interface. -Create and customise a basic SharePoint site. -Set up libraries and lists for content organisation. -Collaboration and Communication:

Enhance teamwork with real-time document sharing. -Integrate SharePoint with Microsoft Teams for seamless collaboration. -Document Management:

Implement best practices for managing documents. -Use metadata and tagging for better organisation. -Explore version control and approval workflows.

Customisation: -Tailor your SharePoint site with themes and web parts. -Understand basic permissions to ensure data security.

Will this be done in just an hr? Join us to find out!

Paul's details: I am an accidental MVP. I have been teaching Microsoft for 20 years and still in shock with my award. I cannot wait share SharePoint tips with you. https://www.linkedin.com/in/paul-pennant/

This event is brought to you in collaboration with the Berlin Practical GenAI Meetup

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Welcome to the GenAI Berlin end of Summer meetup, co-hosted by your friendly GDG Berlin organizers.

If you'd like to give a talk at a future meetup of GenAI Berlin, please fill out this form: https://forms.gle/d52kaHGTCSj7Gjym6

We're looking for hosts! If your company is interested - please DM♥

AGENDA

• 19:00-19:15 Networking over drinks

• 19:15-19:45 Everything you need to know about Google's new Generative AI platform / Gerard Sans

Generative AI has come a long way in the past few months. We all have seen chatbots doing things we couldn't have dreamt of a few years back. Generative AI is today able to process text, images, code and even speech in ways that can help users be more efficient and creative.

For Users, it can access a vast source of information to guide them at work and get more done faster. For Developers, it can explain code snippets, fix your code, help you navigate a new code base or even write tests! The possibilities are endless.

In this talk, you are going to learn about Google's new Generative AI platform Vertex AI, the latest tools (Generative AI Studio) and APIs to foundational models (PaLM2, Imagen, Codey and Chirp), just so you can start building AI-enabled Applications and powerful chatbots. AI's current progress and future is truly exciting!

• 19:45-20:00 Open Mic for hiring, cofounder searching, etc.

• 20:00-20:15 Break

• 20:15-20:45 Large Language Models: A New Era of Augmented Analytics / Paul Egorov

Have you ever seen futuristic films or TV series where humans speak or interact with business intelligence systems using natural language input or even hand gestures? It may have sounded like a dream until 2017 when Google released Cloud Speech-to-Text v1. This opened up a lot of possibilities for building augmented analytics in production. When I worked in consultancy, I built several commercial projects related to this. However, these systems were, to a large extent, rule-based.

Recent advances in Large Language Models (LLMs) have opened up a new era of augmented analytics. We not only know how to convert speech to text, but we can now convert text to code on a contextual level, and it actually works!

In this talk, I would like to elaborate more on the topic of augmented analytics, present a brief history of developments in this field's technical capabilities, share several projects I implemented in this area, and discuss how LLMs revolutionised this field

• 20:45-21:30 Networking

ABOUT OUR SPEAKERS

Gerard Sans | twitter.com/gerardsans

Gerard helps Developers succeed in Artificial Intelligence and Web3. Awarded Google Developer Expert for his community contributions at the GDE Summit 2023 celebrated in Berlin and the Community Connect Europe 2021. He loves running Web3 London, GraphQL London, GraphQL San Francisco, mentoring and giving back to the community.

Paul Egorov | Lead Data Scientist at N26

I am a curious researcher and an enthusiastic leader with a diverse skill set and 9 years of experience in system analytics, entrepreneurship, advanced analytics and deep learning. I have completed more than 15 data science projects in banks / fintech / industry and have been building and managing performant, resilient and learning-oriented teams for 3 years.

ABOUT THE GENAI BERLIN COMMUNITY

We are a community of GenAI enthusiasts.

Join the conference in September: heyai.dev

And follow us on Twitter: twitter.com/heyai_dev

Agenda

Speakers

Gerard Sans

Gerard loves helping Developers to succeed using Web, Cloud, AI and Web3 technologies. He is very excited about the future of the Web and JavaScript. Always happy Computer Science Engineer and humble GDE. He loves to share his learnings by giving talks, training and writing about cool technologies. He loves running Web3 London, GraphQL London, GraphQL San Francisco, mentoring students and givi…

Paul Egorov - N26 (Lead Data Scientist)

I am a curious researcher and an enthusiastic leader with a diverse skill set and 9 years of experience in system analytics, entrepreneurship, advanced analytics and deep learning. I have completed more than 15 data science projects in banks / fintech / industry and have been building and managing performant, resilient and learning-oriented teams for 3 years.

Host

Natalie Pistunovic

Complete your event RSVP here: https://gdg.community.dev/events/details/google-gdg-berlin-presents-genai-berlin-august-meetup/.

This third volume of the best-selling "Data Model Resource Book" series revolutionizes the data modeling discipline by answering the question "How can you save significant time while improving the quality of any type of data modeling effort?" In contrast to the first two volumes, this new volume focuses on the fundamental, underlying patterns that affect over 50 percent of most data modeling efforts. These patterns can be used to considerably reduce modeling time and cost, to jump-start data modeling efforts, as standards and guidelines to increase data model consistency and quality, and as an objective source against which an enterprise can evaluate data models. Praise for The Data Model Resource Book, Volume 3 "Len and Paul look beneath the superficial issues of data modeling and have produced a work that is a must for every serious designer and manager of an IT project." " The Data Model Resource Book, Volume 3: Universal Patterns for Data Modeling is a great source for reusable patterns you can use to save a tremendous amount of time, effort, and cost on any data modeling effort. Len Silverston and Paul Agnewhave provided an indispensable reference of very high-quality patterns for the most foundational types of datamodel structures. This book represents a revolutionary leap in moving the data modeling profession forward." — Ron Powell, Cofounder and Editorial Director of the Business Intelligence Network "After we model a Customer, Product, or Order, there is still more about each of these that remains to be captured, such as roles they play, classifications in which they belong, or states in which they change. The Data Model Resource Book, Volume 3: Universal Patterns for Data Modeling clearly illustrates these common structures. Len Silverston and Paul Agnew have created a valuable addition to our field, allowing us to improve the consistency and quality of our models by leveraging the many common structures within this text." — Steve Hoberman, Best-Selling Author of Data Modeling Made Simple "The large national health insurance company I work at has actively used these data patterns and the (Universal Data Models) UDM, ahead of this book, through Len Silverston’s UDM Jump Start engagement. The patterns have found their way into the core of our Enterprise Information Model, our data warehouse designs, and progressively into key business function databases. We are getting to reuse the patterns across projects and are reaping benefits in understanding, flexibility, and time-to-market. Thanks so much." — David Chasteen, Enterprise Information Architect "Reusing proven data modeling design patterns means exactly that. Data models become stable, but remain very flexible to accommodate changes. We have had the fortune of having Len and Paul share the patterns that are described in this book via our engagements with Universal Data Models, LLC. These data modeling design patterns have helped us to focus on the essential business issues because we have leveraged these reusable building blocks for many of the standard design problems. These design patterns have also helped us to evaluate the quality of data models for their intended purpose. Many times there are a lot of enhancements required. Too often the very specialized business-oriented data model is also implemented physically. This may have significant drawbacks to flexibility. I’m looking forward to increasing the data modeling design pattern competence within Nokia with the help of this book." — Teemu Mattelmaki, Chief Information Architect, Nokia "Once again, Len Silverston, this time together with Paul Agnew, has made a valuable contribution to the body of knowledge about datamodels, and the act of building sound data models. As a professional data modeler, and teacher of data modeling for almost three decades, I have always been aware that I had developed some familiar mental "patterns" which I acquired very early in my data modeling experience. When teaching data modeling, we use relatively simple workshops, but they are carefully designed so the students will see and acquire a lot of these basic "patterns" — templates that they will recognize and can use to interpret different subject matter into data model form quickly and easily. I’ve always used these patterns in the course of facilitating data modeling sessions; I was able to recognize "Ah, this is just like . . .," and quickly apply a pattern that I’d seen before. But, in all this time, I’ve never sat down and clearly categorized and documented what each of these “patterns’’ actually was in such a way that they could be easily and clearly communicated to others; Len and Paul have done exactly that. As in the other Data Model Resource Books, the thinking and writing is extraordinarily clear and understandable. I personally would have been very proud to have authored this book, and I sincerely applaud Len and Paul for another great contribution to the art and science of data modeling. It will be of great value to any data modeler." — William G. Smith, President, William G. Smith & Associates, www.williamgsmith.com "Len Silverston and Paul Agnew’s book, Universal Patterns for Data Modeling, is essential reading for anyone undertaking commercial datamodeling. With this latest volume that compiles and insightfully describes fundamental, universal data patterns, The Data Model Resource Book series represents the most important contribution to the data modeling discipline in the last decade." — Dr. Graeme Simsion, Author of Data Modeling Essentials and Data Modeling Theory and Practice "Volume 3 of this trilogy is a most welcome addition to Len Silverston’s two previous books in this area. Guidance has existed for some time for those who desire to use pattern-based analysis to jump-start their data modeling efforts. Guidance exists for those who want to use generalized and industry-specific data constructs to leverage their efforts. What has been missing is guidance to those of us needing guidance to complete the roughly one-third of data models that are not generalized or industry-specific. This is where the magic of individual organizational strategies must manifest itself, and Len and Paul have done so clearly and articulately in a manner that complements the first two volumes of The Data Model Resource Book. By adding this book to Volumes 1 and 2 you will be gaining access to some of the most integrated data modeling guidance available on the planet." — Dr. Peter Aiken, Author of XML in Data Management and data management industry leader VCU/Data Blueprint