Dave Wentzel

Dave is a Data Solutions Architect with Microsoft. He works with enterprise customers with their digital transformation in the cloud. Dave understands how traditional data and big data fit together to create modern data ecosystems.

Big Data and Hadoop

Saturday, October 22nd, 2016 at 3:00 pm

Don’t know where to start with your Hadoop journey? Is your company considering Hadoop and you want to get up to speed quickly? Just want to modernize your skills? If you answered YES to any of these then this session is for you. Hadoop is a hot skill in the data space but it’s challenging to learn both the new technologies (like Spark and Hive) as well as the modern concepts (like Lambda/Kappa and “streams”). We’ll break down the most important concepts that you need to know and can start using in your job TODAY, even if you don’t have a Hadoop cluster. We’ll do an overview of the important tooling and show you how to spin up a sandbox in minutes.

Practical DevOps Using Azure DevTest Labs

Saturday, October 22nd, 2016 at 11:30 am

Azure DevTest Labs is a great way to solve common development environment challenges. Self-service deployment can be done quickly AND cost-effectively. By using templates, artifacts, and “formulas” you can deploy the latest version of your application, whether Windows or Linux. This is great for development, testing, training, demos, and even lightweight DR environments. We’ll show you how to get started with DevTest Labs regardless of whether you use Visual Studio.

So You Want to Be a Data Scientist?

Wednesday, September 21st, 2016 at 5:30 pm

Does R seem like an alien language to you? Does data science terminology seem overly confusing? Would you like to learn more about data science but are scared of the math? Fact is, you’re probably doing “data science” today. You don’t need to know a lot of R or python to be an effective data scientist. We’ll cover important terminology and use cases and then dive-in by exploring data with tools you are already using. We’ll deploy a modern data science workstation in just 10 minutes. Finally, we’ll put it all together and create a predictive web service using Azure Machine Learning.