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Building the Databricks Lakehouse

Join the Databricks Bootcamps, taking place in a city near you. 

Led by Databricks instructors, these sessions will use real-world data sets as we go under the hood to demonstrate how to use robust technologies such as Delta Lake, Databricks SQL and MLflow. 

This program offers two days of content, where you are welcome to attend both days or just the session most relevant to your priorities. 

Free to attend, these technical hands-on workshops are suited for data practitioners in data engineering, data science, analytics and BI. Gain a better understanding of how Databricks Lakehouse supports data and AI initiatives and allows practitioners to work more collaboratively and innovate faster. No immediate knowledge of Databricks is required.

Day 1: Building the Lakehouse - with  Data Engineering 

Time: 09:00-17:00 

This full-day session will cover the foundations of Databricks’ core platform and data engineering workloads. You will get practical advice and best-practice tips for how to use powerful open source technologies, such as Delta Lake, with governance frameworks like Unity Catalog. We will also cover Delta Sharing - an open protocol for secure real-time sharing of data. Furthermore, we will demonstrate how Delta Live Tables (DLT) makes it easy to build and deploy reliable data pipelines at scale. The agenda will be a mix of technology deep dives and hands-on labs.

Who should attend: Suited for data engineering professionals and platform owners

Day 2: Consumption of Lakehouse - with Databricks SQL and Machine Learning 

Time: 09:00-17:00 

In this full-day session, you will learn to build the best warehouse on your lakehouse. Using Databricks SQL, you will learn how to bring all your data together to create reporting and BI analytics. You will see the benefits of Databricks SQL Serverless and how you can integrate it with BI tools like Power BI for high-impact analytics and insights. Further, we will dive into building analytical models for both data scientists and citizen developers. We will demonstrate managing the complete machine learning lifecycle - from experimentation, AutoML, model management, deployment and model productionisation. 

Who should attend: Suited for machine learning engineers, data science, business analytics, and data architects. 

Please ensure to bring a laptop (and charger) in order to participate in the hands-on labs. 

Limited seats are available for these workshops. Please ensure to secure a seat by registering.

Where and when

Sydney
28 March: Data Engineering 9:00 AM - 5:00 PM AEST
29 March: Databricks SQL + Machine Learning 9:00 AM - 5:00 PM AEDT
Venue: Cliftons, 13/60 Margaret St

Melbourne 
29 March: Data Engineering 9:00 AM - 5:00 PM AEST
30 March: Databricks SQL + Machine Learning 9:00 AM - 5:00 PM AEDT
Venue: Cliftons, 1/440 Collins St 

Auckland
2 May: Data Engineering 9:00 AM - 5:00 PM NZDT
3 May: Databricks SQL + Machine Learning 9:00 AM - 5:00 PM NZST
Venue: Cliftons, 4/45 Queen St

Adelaide 
3 May: Data Engineering 9:00 AM - 5:00 PM ACST
4 May: Databricks SQL + Machine Learning 9:00 AM - 5:00 PM ACST
Venue: Cliftons, 1/80 King William St

Brisbane
9 May: Data Engineering 9:00 AM - 5:00 PM AEST
10 May: Databricks SQL + Machine Learning 9:00 AM - 5:00 PM AEST
Venue: Cliftons, 24/288 Upper Edward St

Wellington
10 May: Data Engineering 9:00 AM - 5:00 PM NZST
11 May: Databricks SQL + Machine Learning 9:00 AM - 5:00 PM NZDT
Venue: Terrace Conference Centre, 114 The Terrace, Wellington Central

Perth
16 May: Data Engineering 9:00 AM - 5:00 PM AWST
17 May: Databricks SQL + Machine Learning 9:00 AM - 5:00 PM AWST
Venue: Cliftons, Parmelia House, 191 St Georges Terrace