Workshop Databricks – Operationalizing Machine Learning on the Lakehouse

In this session we walk you through the process of operationalizing machine learning on the Databricks Lakehouse. We will leverage Delta Live Tables to define end-to-end data pipelines by specifying the data source, the transformation logic and destination state of the data. We will then focus on the application of advanced time-series techniques and introduce a scalable pipeline using MLOps that allows us to solve forecasting problems using multiple forecasting techniques and frameworks.

Outline: 90 minutes

  • 10 min. – Big Picture Lakehouse
  • 40 min. – Delta Live Tables
  • 40 min. – MLOps + Time Series Forecasting


Tania Sennikova, Solutions Architect | Databricks

Tania Sennikova is a Solutions Architect, working in the Field Engineering team of Databricks. She supports customers on building scalable cloud architectures for Data Science use cases. Her subject matter expertise is Time Series Analysis and Forecasting. Prior to Databricks, Tania worked as a Data Science Consultant building data driven solutions for the automotive industry.

Ivan Trusov, Specialist Solutions Architect | Databricks

Ivan Trusov is a Specialist Solutions Architect, working in the EMEA team of Databricks in Berlin.He assists customers to build, scale and operate data and ML applications on the Databricks Lakehouse platform. Prior to Databricks, Ivan worked as a Data Engineer at Zalando, and has in total 5 years of experience building scalable ML and Data applications.

Bram Rodenburg, Senior Solutions Consultant | Databricks

Bram Rodenburg is a Senior Solutions Consultant, working in the Professional Services team of Databricks in Munich. Supporting customers in setting up their Databricks Lakehouse Platform, and bringing data pipelines and machine learning models into production. Prior to Databricks, Bram worked as a Data Engineer at Lynx Analytics, a start-up, focused on building data pipelines for the LynxKite large-scale graph analysis product.

Volker Tjaden, Team Lead Specialist Solution Architects | Databricks

Volker leads a team of Specialist Solutions Architects at Databricks. His career in Data & AI started out as an economics student at university where he focused on statistical and computational methods working with large datasets. After completing a PhD, he held various consulting and management positions in different industries where he built data driven solutions to business problems such as dynamic pricing in banking, automated supply chains in retail and IoT platforms in manufacturing.