Details

PBIMCR Jan 2025 Meetup

When: Thursday 30th of Jan 2025 Time: arrive for 5:30pm with talks starting from 6pm start prompt Location: Manchester Technology Centre, Oxford Road Session will not be streamed over MS Teams Complimentary Drinks and Pizza will be provided by our long-time sponsor Robert Walters https://www.robertwalters.co.uk/our-stories/power-bi-manchester-user-group.html

Speaker: Juliana Smith

Topics: Implementing alternative accessible colours in Power BI Reports

This session highlights the importance of accessible colour usage and compliance with WCAG guidelines, offering a concise overview of Power BI’s accessibility considerations. I will also present a practical solution that allows users to toggle between standard and accessible views, ensuring reports are optimised for individuals with vision impairments. By making these adjustments, we can create more inclusive, user-friendly reports for everyone

2nd speaker Ian Pike and David Mitchell from Microsoft

They will give us the latest news from Micrsoft Ignite conference with updates on Fabric and what 2025 has instore...

The past few days, you have heard about many new developments in the AI space, from new models and capabilities to autonomous agents. In this session, we will recap the concepts, tools, and frameworks covered this week that you'll need to build your AI solutions for tomorrow.

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Henk Boelman * Daniel Laskewitz * David Smith

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Ignite 2024 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com

BRK132 | English (US) | AI

MSIgnite

Our next PBI BRUM meetup will be on Tuesday 7th November! We will be joined by David Smith who will be delivering a case study on his lessons learnt from a Power BI implementation project & Jon Lunn who will be covering the what and why of Microsoft Fabric!

For the first time, we will have both speakers in person, there will be plenty of engaging and collaborative content for you to enjoy. It is also the first time we are having a case study delivered so we are excited for this one!

17:45 - Welcome & networking

18:00 - Introductions

18:10 - David Smith with lessons learnt from a Power BI implementation project: Presentation summary Implementing Power BI to modernise large legacy reporting stacks is a significant change activity. He will cover the case for change, the approach to delivery, and the lessons learnt. He will discuss when things go wrong, how can you manage implementation risks?

18:50 - Break

19:15 - Jon Lunn with the what and why of Microsoft Fabric: Overview of some of the features in MS Fabric, and why they matter to Power BI developers. Looking mostly at the Data Engineering process he'll demo pipelines and Direct Lake connections. He'll also be speaking about why this new data platform service has evolved, and what it means for the future.

20:00 - Finish

About this series: Microsoft Reactor’s Make Azure AI Real series is a collection of AI livestreams that are focused on AI technical content from experts at Microsoft. You will learn how to use Microsoft AI tools and services, such as Azure Cognitive Services, Azure OpenAI Service, and more. You will also get insights into the latest AI trends and best practices from Microsoft AI experts. Join us for this exciting series and discover how to make AI real for your projects and goals.

About this session: In this lab led by David Smith and Korey Stegared-Pace, you will understand the capabilities of Azure OpenAI Service and learn how to use and customize natural language generative AI models like GPT-3.5 and ChatGPT.

Our guest this week is Hamilton physics professor Kate Jones-Smith who joins us to discuss the evidence for the claim that drip paintings of Jackson Pollock contain fractal patterns. This hypothesis originates in a paper by Taylor, Micolich, and Jonas titled Fractal analysis of Pollock's drip paintings which appeared in Nature. 

Kate and co-author Harsh Mathur wrote a paper titled Revisiting Pollock's Drip Paintings which also appeared in Nature. A full text PDF can be found here, but lacks the helpful figures which can be found here, although two images are blurred behind a paywall. 

Their paper was covered in the New York Times as well as in USA Today (albeit with with a much more delightful headline: Never mind the Pollock's [sic]). 

While discussing the intersection of science and art, the conversation also touched briefly on a few other intersting topics. For example, Penrose Tiles appearing in islamic art (pre-dating Roger Penrose's investigation of the interesting properties of these tiling processes), Quasicrystal designs in art, Automated brushstroke analysis of the works of Vincent van Gogh, and attempts to authenticate a possible work of Leonardo Da Vinci of uncertain provenance. Last but not least, the conversation touches on the particularly compellingHockney-Falco Thesis which is also covered in David Hockney's book Secret Knowledge. 

For those interested in reading some of Kate's other publications, many Katherine Jones-Smith articles can be found at the given link, all of which have downloadable PDFs.

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