VDUG is a community of data enthusiasts who come together once a month to share, learn and grow our Databricks and data optimization skills. Each meeting Databricks Champion leaders and attendees share best practices, practical takeaways and real-world success stories.
Meetings the last Tuesday of each month!
Topics of the presentation will vary month to month covering new platform updates, best practice demos, and solutions for common challenges. Keep an eye on the schedule below for more details on each month’s presentation.
An open discussion in which attendees can ask questions, share their own experiences and seek guidance on their unique challenges using Databricks and associated technologies.
Interactive behind the scenes DataBricks engineering lifecycle sessions including coding, research and debugging. Go deeper and get your questions answered live with VDUG Host, Valorem Data Scientist and Databricks Champion, Spencer Cook!
Azure Cognitive Services
Azure Data Factory
Azure Data Lake Gen2
Azure Event Hub
Azure IoT Hub
Azure Machine Learning
Azure Synapse Analytics
Azure SQL Server
Databricks Delta Lake
Databricks ML Flow
MS Power BI
VDUG attendees will have access to exclusive training opportunities with experienced data professionals each month. Databricks Champions share “been there, done that” tips with attendees and demo new solutions and capabilities.
Meet other Databricks users in similar roles, facing similar challenges to build a strong network of support to help you grow your Databricks experience and skills.
Pick up new data strategies and solutions you can implement right away to get more out of your data, improve organizational insight and have a real impact on your business.
April 28th, 2020
Databricks Champion, Spencer Cook will demonstrate how to use Databricks Structured Streaming to poll data from the Twitter API and stream it into Azure Event Hub. Then stream the data back out of Event Hub and enrich it using Azure Cognitive Services before loading it into a Databricks Delta Lake table.
May 26th, 2020
In this session we will discuss a new paradigm emerging in data work, the Data Lakehouse. We will look at what is different about this approach and the advantages it has over the traditional Data Warehouse/Lake. Followed by a discussion on how Databricks Delta facilitates these features and what architectural features of the Databricks Platform facilitate a Data Lakehouse.
June 30th, 2020
Learn how MLflow can help you manage your machine learning lifecycle at enterprise scale. We will dig into the core components of MLflow including: Tracking, Projects, Models, and Registry. Then look at how to use the tracking and model components to cross-validate and deploy a model.