Introducing Databricks Ingest: Easy and Efficient Data Ingestion from Different Sources into Delta Lake
Get an early preview of O'Reilly's new ebook for the step-by-step guidance you need to start using Delta Lake We are excited to...
Working with Entity Relationship (ER) Diagrams on Databricks
Introduction Databricks supports the standard SQL data types and has first-class support for both ODBC and JDBC clients. This means that most 3rd...
On-Demand Webinar: Granular Demand Forecasting At Scale
We recently hosted a live webinar — How Starbucks Forecasts Demand at Scale with Facebook Prophet and Databricks — During this webinar we...
How to Display Model Metrics in Dashboards using the MLflow Search API
Machine learning engineers and data scientists frequently train models to optimize a loss function. With optimization methods like gradient descent, we iteratively improve...
Automating Digital Pathology Image Analysis with Machine Learning on Databricks
Check out our solution accelerator for automating digital pathology analysis or watch our on-demand webinar to learn more. With technological advancements in imaging...
What Is a Lakehouse?
Read Building the Data Lakehouse to explore why lakehouses are the data architecture of the future with the father of the data warehouse...
Query Delta Lake Tables from Presto and Athena, Improved Operations Concurrency, and Merge performance
Get an early preview of O'Reilly's new ebook for the step-by-step guidance you need to start using Delta Lake. We are excited to...
On-Demand Webinar: Geospatial Analytics and AI in the Public Sector
We recently hosted a live webinar — Geospatial Analytics and AI in Public Sector — during which we covered top geospatial analysis use...
Fine-Grained Time Series Forecasting At Scale With Facebook Prophet And Apache Spark
Try this time series forecasting notebook in our Solution Accelerator for Demand Forecasting . Advances in time series forecasting are enabling retailers to...
Solving the World’s Toughest Problems with the Growing Open Source Ecosystem and Databricks
We started Databricks in 2013 in a tiny little office in Berkeley with the belief that data has the potential to solve the...