A Comprehensive Look at Dates and Timestamps in Apache Spark™ 3.0
Apache Spark is a very popular tool for processing structured and unstructured data. When it comes to processing structured data, it supports many...
Analyzing Customer Attrition in Subscription Models
Download the notebooks to demo the solution covered below The subscription model is experiencing a renaissance. Gone are the days of the penny...
How to Extract Market Drivers at Scale Using Alternative Data
Watch the on-demand webinar Alternative Data Analytics with Python for a demonstration of the solution discussed in this blog and/or download the following...
A Data-driven Approach to Environmental, Social and Governance
The future of finance goes hand in hand with social responsibility, environmental stewardship and corporate ethics. In order to stay competitive, Financial Services...
Allow Simple Cluster Creation with Full Admin Control Using Cluster Policies
What is a Databricks cluster policy? A Databricks cluster policy is a template that restricts the way users interact with cluster configuration. Today...
Announcing GPU-aware scheduling and enhanced deep learning capabilities
Databricks is pleased to announce the release of Databricks Runtime 7.0 for Machine Learning (Runtime 7.0 ML) which provides preconfigured GPU-aware scheduling and...
Announcing MLflow Model Serving on Databricks
Databricks MLflow Model Serving provides a turnkey solution to host machine learning (ML) models as REST endpoints that are updated automatically, enabling data...
Time Traveling with Delta Lake: A Retrospective of the Last Year
Get an early preview of O'Reilly's new ebook for the step-by-step guidance you need to start using Delta Lake. Try out Delta Lake...
Customer Lifetime Value Part 2: Estimating Future Spend
Check out the notebook referred throughout the blog and watch the on-demand virtual workshop to learn more. You can also go to Part...
Simplify Python environment management on Databricks Runtime for Machine Learning using %pip and %conda
Today we announce the release of %pip and %conda notebook magic commands to significantly simplify python environment management in Databricks Runtime for Machine...