Applied analytics with Azure Databricks using Databricks SQL and Databricks machine learning

Lakehouse architecture simplifies the use of big data. With Databricks SQL, data analytics over many different data sources can be simplifies and make easy.

Azure databricks have been around for a long time and every year we get great new updates, features and patches that make data analytics faster, easier and more efficient. This time around, we will look into Machine learning with Scala, Python and R and Databricks SQL - the new features in the bunch. Databricks SQL comes with the lakehouse architecture, supporting not only data from different sources but also real-time data ingestion (delta lake) and other Azure data source. With a given dataset, we will walk through a couple of notebooks, scripts and SQL code and give the attendees an insightful journey.

Speaker

Microsoft Data Platform MVP, BI/DEV with 20+ years of background with statistics and math and more than 15+ years of MS SQL experience. Frequent speaker at SQL Saturday events and local user groups and Microsoft related events (PASS, 24HOP).

Tomaž Kaštrun's Sessions

Common Data Science Mistakes

Addressing climate change with help of Machine learning

Applied analytics with Azure Databricks using Databricks SQL and Databricks machine learning

Azure Machine Learning Service with Python

Notebooks - standardized enterprise solution for better story telling.

Analyzing database with XE and Query Store data using R / Py

Common Data Science Mistakes