Common Data Model

After we recorded Episode 189, we knew we lacked some of the business reasons behind the Common Data Model. Luckily, we reached out Tricia Wilcox-Almas and she has helped us fill in some of the gaps and also present how the Common Data Model is implemented in the new versions of Azure Data Lake.

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Listen to Learn

00:27     Intro to the guest and topic
02:36     How the Common Data Model came to be and what it is
04:26     The first data warehouse that Tricia ever worked on
06:55     Things have changed drastically since then
08:54     Where adoption has been seen so far
12:41     CDM doesn’t make sense on the SQL side of things
15:04     What DBAs are possibly destined to end up doing
16:18     The nickel tour of the Common Data Model
19:57     The difference between Azure Blob Storage and Azure Data Lake Storage Gen2
22:01     Graph is probably the next big thing
22:55     Eugene’s thoughts on where CDM came from
25:06     The Common Data Model makes data use easier for end-users
26:13     Some last thoughts on the conversation
27:29     SQL Family Questions
34:25     Compañero Shout-Outs
36:05     Closing Thoughts & Contact Info

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The Common Data Model is a collaborative experiment between Adobe, SAP and Microsoft…and the hope there is that this better integration is going to lead to better insights, better data.

Tricia Wilcox-Almas

Meet the Hosts

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Carlos Chacon

With more than 10 years of working with SQL Server, Carlos helps businesses ensure their SQL Server environments meet their users’ expectations. He can provide insights on performance, migrations, and disaster recovery. He is also active in the SQL Server community and regularly speaks at user group meetings and conferences. He helps support the free database monitoring tool found at and provides training through SQL Trail events.

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Eugene Meidinger

Eugene works as an independent BI consultant and Pluralsight author, specializing in Power BI and the Azure Data Platform. He has been working with data for over 8 years and speaks regularly at user groups and conferences. He also helps run the GroupBy online conference.

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Kevin Feasel

Kevin is a Microsoft Data Platform MVP and proprietor of Catallaxy Services, LLC, where he specializes in T-SQL development, machine learning, and pulling rabbits out of hats on demand. He is the lead contributor to Curated SQL, president of the Triangle Area SQL Server Users Group, and author of the books PolyBase Revealed (Apress, 2020) and Finding Ghosts in Your Data: Anomaly Detection Techniques with Examples in Python (Apress, 2022). A resident of Durham, North Carolina, he can be found cycling the trails along the triangle whenever the weather's nice enough.

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