Databricks

Azure Training Webinar Series

Azure Databricks is a first-party Microsoft solution that can support the full range of data engineering and data science activities, including data management and transformation, streaming analytics, and machine learning. In this three-part training series, we’ll teach you how to get started with Azure Databricks, begin to understand its capabilities and how to put it into production in your own infrastructure to run workloads 10-100x faster than non-Databricks platforms, with the security and scale of Azure.

You should consider attending these sessions if you are a data engineer or data scientist interested in learning to use Azure Databricks, and how it can make an impact on your team.

The three training sessions are

  • Azure Databricks Training: Data Engineering
  • Azure Databricks Training: Streaming Analytics
  • Azure Databricks Training: Data Science

These trainings can be attended as a set or individually based on your needs and interest. We recommend attending all three to get a fuller understanding of what is possible with Azure Databricks.

Azure Databricks Training: Data Engineering

In this training, we’ll teach you how to build your own Azure Databricks ETL pipeline, starting with ingestion, moving through transformation, and loading your data into a SQL Data Warehouse. Learn about how easy it is to use Azure Databricks and how you can run workloads up to 10-100x faster than non-Databricks platforms.

During this session we will cover

  • Batch ingest using Databricks
  • How to transform data using Spark SQL and DataFrames
  • Using the SQL Data Warehouse connector to load data into SQL Data Warehouse
 
 

Azure Databricks Training: Streaming Analytics

In the second training of our Azure Databricks Training series, we’ll teach you how to connect directly to data sources like TCP/IP sockets and the Kafka messaging system, transform and output data, and finally create compelling continuously-updated visualizations to drive greater impact for your teams.

During this session we will cover

  • Connecting to TCIP and Kafka as streaming sources
  • Use the DataFrame API to transform streaming data
  • Output the results to various sinks
  • Use Databricks visualization feature to create a continuously updated visualization of processed streaming data.

Azure Databricks Training: Data Science

In the third of the three-part training series, we’ll show you how you can use MLlib with Azure Databricks to train your own models, run replicable experiments, and deploy into production with fewer failing jobs to accelerate your organization’s data science efforts. 

During this session we will cover

  • Estimators, Transformers and ML Pipelines
  • How to train an ML Model
  • How to save and read an ML Model
  • How to make predictions with an ML Model