6 Guiding Principles to Build an Effective Data Lakehouse
In this blog post, we will discuss some guiding principles to help you build a highly-effective and efficient data lakehouse that delivers on…
Best Practices
Architecting MLOps on the Lakehouse
Here at Databricks, we have helped thousands of customers put Machine Learning (ML) into production. Shell has over 160 active AI projects saving…
Databricks on Google Cloud Security Best Practices
The lakehouse paradigm enables organizations to store all of their data in one location for analytics, data science, machine learning (ML), and business…
Dominate Your Daily Wordle With Lakehouse
Since it launched late last year, Wordle has become a daily highlight for people around the world. So much, that the New York…
Functional Workspace Organization on Databricks
Introduction This blog is part one of our Admin Essentials series, where we’ll focus on topics that are important to those managing and…
Beyond LDA: State-of-the-art Topic Models With BigARTM
This post follows up on the series of posts in Topic Modeling for text analytics. Previously, we looked at the LDA (Latent Dirichlet…
4 Ways AI Can Future-proof Financial Services’ Risk and Compliance
Learn more about Smarter risk and compliance on our new hub. The core function of a bank is to protect assets, identify risks…
5 Key Steps to Successfully Migrate From Hadoop to the Lakehouse Architecture
The decision to migrate from Hadoop to a modern cloud-based architecture like the lakehouse architecture is a business decision, not a technology decision.…
Considerazioni principali per la migrazione da Hadoop
Apache Hadoop was created more than 15 years ago as an open source, distributed storage and compute platform designed for large data sets…
How We Launched a Podcast: Lessons, (Minor) Mishaps & Key Takeaways
After six episodes featuring amazing leaders and practitioners in the data and AI community, we wrapped up season 1 of Data Brew by…
