Over the years I have presented a ton (see the list), and some of those presentations were recorded. I had put some of them on my YouTube channel, but neglected to post some of them (13 in fact). They are now all there, and below I highlighted a few that I hope you will find helpful. If you do find any helpful, please subscribe to my YouTube channel to be notified of new videos, and I’ll make sure to upload any future recordings withing a few days of the event:

Data Lakehouse, Data Mesh, and Data Fabric (1 hour) – Calgary Azure Analytics User Group

(view) So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a modern data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. They all may sound great in theory, but I’ll dig into the concerns you need to be aware of before taking the plunge. I’ll also include use cases so you can see what approach will work best for your big data needs. And I’ll discuss Microsoft version of the data mesh.

Data Lakehouse, Data Mesh, and Data Fabric (10 minute overview) – DataMinutes

(view) So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a modern data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. They all may sound great in theory, but I’ll dig into the concerns you need to be aware of before taking the plunge. I’ll also include use cases so you can see what approach will work best for your big data needs. And I’ll discuss Microsoft version of the data mesh.

Data Lakehouse: Debunking the Hype

(view) In this podcast I talked about data warehouse, data lakehouse, and the differences.

The Rise of Data Mesh: Panel discussion – James Serra – Decisive 2022 

(view) I was on a panel for the conference Decisive 2022 and discussed the data mesh.

Interview on data mesh and data warehousing – James Serra – UNION: The Data Fest 

(view) In this interview for the UNION conference I talked about my thoughts on data mesh, data warehousing, Microsft Purview, and Microsoft’s approach to competition

Big Data Architectures and The Data Lake – PASS Cloud Virtual Group

(view) 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!

Data Warehousing Trends, Best Practices, and Future Outlook

(view) 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 presentation 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