James Serra
Big Data/Data Warehouse Evangelist at Microsoft
Ponte Vedra Beach, Florida, United States
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James works at Microsoft as a big data and data warehousing solution architect where he has been for most of the last nine years. He is 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 he was an independent consultant working as a Data Warehouse/Business Intelligence architect and developer. He is a prior SQL Server MVP with over 35 years of IT experience. He is a popular blogger (JamesSerra.com) and speaker, having presented at dozens of major events including SQLBits, PASS Summit, Data Summit and the Enterprise Data World conference. He is the author of the book “Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh”.
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Data Architectures and Microsoft Fabric
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. In this presentation, I will give you a guided tour of each architecture to help you understand its pros and cons. I will also examine common data architecture concepts, including data warehouses and data lakes. 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.
In addition, I will delve into how Microsoft Fabric can be leveraged within each of these architectures. From integrating data fabrics for enhanced data management and governance, to implementing data lakehouses for streamlined analytics, and establishing data meshes for decentralized data ownership, Microsoft Fabric offers robust solutions and tools. By the end of this presentation, you’ll have a clear understanding of how to use Microsoft Fabric to build and optimize these diverse data architectures, tailored to meet your specific requirements.
Should I move my database to the cloud?
So you have been running on-prem SQL Server for a while now. Maybe you have taken the step to move it from bare metal to a VM, and have seen some nice benefits. Ready to see a TON more benefits? If you said “YES!”, then this is the session for you as I will go over the many benefits gained by moving your on-prem SQL Server to an Azure VM (IaaS). Then I will really blow your mind by showing you even more benefits by moving to Azure SQL Database (PaaS/DBaaS). And for those of you with a large data warehouse, I also got you covered with Azure SQL Data Warehouse. Along the way I will talk about the many hybrid approaches so you can take a gradual approach to moving to the cloud. If you are interested in cost savings, additional features, ease of use, quick scaling, improved reliability and ending the days of upgrading hardware, this is the session for you!
Microsoft fabric and data mesh
Do you want to use Microsoft Fabric to build a data mesh? And how would that be different than using Microsoft Fabric to build a data lakehouse or data fabric? In this session I will discuss how to "configure" Fabric to work within a data mesh and clarify the definitions of various data architectures and how to use Fabric for each of them.
I will discuss what a pure data mesh is, why pure data mesh’s are not being built, why Modern Analytics and Governance (MAG) at Scale is what is being built instead of a pure data mesh, and how Microsoft Fabric can be used for MAG at Scale.
Microsoft Fabric introduction
Microsoft Fabric is the next version of Azure Data Factory, Azure Data Explorer, Azure Synapse Analytics, and Power BI. It brings all of these capabilities together into a single unified analytics platform that goes from the data lake to the business user in a SaaS-like environment. Therefore, the vision of Fabric is to be a one-stop shop for all the analytical needs for every enterprise and one platform for everyone from a citizen developer to a data engineer. Fabric will cover the complete spectrum of services including data movement, data lake, data engineering, data integration and data science, observational analytics, and business intelligence. With Fabric, there is no need to stitch together different services from multiple vendors. Instead, the customer enjoys end-to-end, highly integrated, single offering that is easy to understand, onboard, create and operate.
This is a hugely important new product from Microsoft and I will simplify your understanding of it via a presentation and demo.
Agenda:
What is Microsoft Fabric?
Workspaces and capacities
OneLake
Lakehouse
Data Warehouse
ADF
Power BI / DirectLake
Resources
Learning to present and becoming good at it
Have you been thinking about presenting at a user group? Are you being asked to present at your work? Is learning to present one of the keys to advancing your career? Or do you just think it would be fun to present but you are too nervous to try it? Well take the first step to becoming a presenter by attending this session and I will guide you through the process of learning to present and becoming good at it. It’s easier than you think! I am an introvert and was deathly afraid to speak in public. Now I love to present and it’s actually my main function in my job at Microsoft. I’ll share with you journey that lead me to speak at major conferences and the skills I learned along the way to become a good presenter and to get rid of the fear. You can do it!
How to build your career
In three years I went from a complete unknown to a popular blogger, speaker at PASS Summit, a SQL Server MVP, and then joined Microsoft. Along the way I saw my yearly income triple. Is it because I know some secret? Is it because I am a genius? No! It is just about laying out your career path, setting goals, and doing the work.
I’ll cover tips I learned over my career on everything from interviewing to building your personal brand. I’ll discuss perm positions, consulting, contracting, working for Microsoft or partners, hot fields, in-demand skills, social media, networking, presenting, blogging, salary negotiating, dealing with recruiters, certifications, speaking at major conferences, resume tips, and keys to a high-paying career.
Your first step to enhancing your career will be to attend this session! Let me be your career coach!
Enhancing your career: Building your personal brand
In three years I went from a complete unknown to a popular blogger, speaker at PASS Summit, and a SQL Server MVP. Along the way I saw my yearly income triple. Is it because I know some secret? Is it because I am a genius? No! It is just about laying out your career path, setting goals, and doing the work. It’s about building your personal brand and stepping out of your comfort zone. It’s about overcoming your fear of taking risks. If you can do those things, you will be rewarded. I will discuss how you too can go from unknown to well-known. I will talk about building your community presence by blogging, presenting, writing articles and books, twitter, LinkedIn, certifications, interviewing, networking, and consulting and contracting. Your first step to enhancing your career will be to attend this session!
Deciphering Data Architectures full-day workshop
This pre-conference workshop will begin by defining 'big data' and clarifying various data architecture concepts to establish a solid foundation of understanding before delving into specific data architectures. Topics to be covered include relational data warehouses, data lakes, data marts, data virtualization, and the differences between ETL and ELT. James will then explore and compare the architectures of the Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh in considerable detail, highlighting their advantages and disadvantages. While these concepts may seem appealing in theory, James will address potential concerns to consider before implementation. This workshop aims to demystify these complex topics, offering ample opportunity for questions. The content is derived from James's book "Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh."
Deciphering Data Architectures (Modern Data Warehouse, Data Fabric, Data Lakehouse, Data Mesh)
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. In this presentation I will give you a guided tour of each architecture to help you understand its pros and cons. I will also examine common data architecture concepts, including data warehouses and data lakes. 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. And I’ll finish with discussing Microsoft’s version of the data mesh.
Data Lake Overview
The data lake has become extremely popular, but there is still confusion on how it should be used. In this presentation I will cover common big data architectures that use the data lake, the characteristics and benefits of a data lake, and how it works in conjunction with a relational data warehouse. Then I’ll go into details on using Azure Data Lake Store Gen2 as your data lake, and various typical use cases of the data lake. As a bonus I’ll talk about how to organize a data lake and discuss the various products that can be used in a modern data warehouse.
Data Warehousing Trends, Best Practices, and Future Outlook
Over the last decade, the 3Vs of data – Volume, Velocity & Variety has grown massively. The Big Data revolution has completely changed the way companies collect, analyze & store data. Advancements in cloud-based data warehousing technologies have empowered companies to fully leverage big data without heavy investments both in terms of time and resources. But, that doesn’t mean building and managing a cloud data warehouse isn’t accompanied by any challenges. From deciding on a service provider to the design architecture, deploying a data warehouse tailored to your business needs is a strenuous undertaking. Looking to deploy a data warehouse to scale your company’s data infrastructure or still on the fence? In this presentation you will gain insights into the current Data Warehousing trends, best practices, and future outlook. Learn how to build your data warehouse with the help of real-life use-cases and discussion on commonly faced challenges. In this session you will learn:
- Choosing the best solution – Data Lake vs. Data Warehouse vs. Data Mart
- Choosing the best Data Warehouse design methodologies: Data Vault vs. Kimball vs. Inmon
- Step by step approach to building an effective data warehouse architecture
- Common reasons for the failure of data warehouse implementations and how to avoid them
Data lake design
There is no "one shoe fits all" when it comes to designing a data lake. All cover all the options around layers, folders, best practices, performance considerations, and cost considerations.
Big data architectures and the data lake
With so many new technologies it can get confusing on the best approach to building a big data architecture. The data lake is a great new concept, usually built in Hadoop, but what exactly is it and how does it fit in? In this presentation I’ll discuss the four most common patterns in big data production implementations, the top-down vs bottoms-up approach to analytics, and how you can use a data lake and a RDBMS data warehouse together. We will go into detail on the characteristics of a data lake and its benefits, and how you still need to perform the same data governance tasks in a data lake as you do in a data warehouse. Come to this presentation to make sure your data lake does not turn into a data swamp!
James Serra
Big Data/Data Warehouse Evangelist at Microsoft
Ponte Vedra Beach, Florida, United States
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