Welcome to the July 17th 1800 HRS PST/2100 HRS EST, 2024 HYBRID meeting!
We are once again meeting in person in Vancouver, WA at the downtown Umpqua Bank in their Community Room!
We meet on the 3rd Wednesday of the month once again at 6:00 PM PST. We will have snacks and networking before the main meeting.
But… we will continue to operate monthly online meetings through the PNW collaborative facilitated by the Oregon Data Community. Due to this, you will be able to attend the meeting remotely and we are definitely open to remote speakers.
Please Register at Meetup!!!
https://www.meetup.com/oregonsql/events/302102071
In order to encourage questions during the presentation, please use chat which will be monitored and/or use the raise hands option in Teams. Please be mindful of the other attendees and mute your mic!
We will be starting at 6:00 PM PST/9:00 PM EST
Schedule: (may be fluid due to discussions and Q/A):
6:00 – 6:30 PM – Snacks/Announcements/Networking
6:30 PM – Presentation
8:30 PM – Happy Hour/Networking (Shanahans in Vancouver)
Presentation:
Title: Deciphering Data Architectures
Abstract:
Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they’re also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of these architectures to help data professionals understand the pros and cons of each.
James Serra, big data and data warehousing solution architect at Microsoft, examines common data architecture concepts, including how data warehouses have had to evolve to work with data lake features. You’ll learn what data lakehouses can help you achieve, and how to distinguish data mesh hype from reality. Best of all, you’ll be able to determine the most appropriate data architecture for your needs. With this book, you’ll:
- Gain a working understanding of several data architectures
- Learn the strengths and weaknesses of each approach
- Distinguish data architecture theory from the reality
- Pick the best architecture for your use case
- Understand the differences between data warehouses and data lakes
- Learn common data architecture concepts to help you build better solutions
- Explore the historical evolution and characteristics of data architectures.
- Learn essentials of running an architecture design session, team organization, and project success factors
- Free from product discussions, this book is a timeless resource for years to come
Bio:
I work at Microsoft as a big data and data warehousing solution architect where I have been for most of the last nine years. I am a thought leader in the use and application of Big Data and advanced analytics, including data architectures such as the modern data warehouse, data lakehouse, data fabric, and data mesh. Previously I was an independent consultant working as a Data Warehouse/Business Intelligence architect and developer. I am a prior SQL Server MVP with nearly 40 years of IT experience. I started my career as a software developer, then was a DBA for 12 years, and for the last twelve years I have been working extensively with business intelligence and data warehousing using numerous Microsoft technologies and tools. I have been at times a permanent employee, consultant, contractor, and owner of my own business. All these experiences along with continuous learning have helped me to develop many successful data warehouse and BI projects. I am a popular blogger and speaker, having presented at dozens of major events including SQLBits, PASS Summit, Data Summit, SQLDay and the Enterprise Data World conference. I am the author of the book “Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh“. I have numerous Microsoft certifications, and have a Bachelor of Science degree in Computer Engineering from the University of Nevada-Las Vegas. More info is at http://www.linkedin.com/in/jamesserra
If you are looking for thought leadership, strategy, or advice on big data, including data architectures such as the modern data warehouse, data lakehouse, data fabric, or data mesh, please contact me. I have experience in both the theory side and the implementation side.
