Databricks

What is Databricks?

Databricks is a Data Intelligence Platform built on an open lakehouse architecture. It provides a single place for all your data and governance, combined with AI models tailored to your organization. Non-technical users can explore data using automation and natural language, while technical teams can build and deploy secure data and AI applications.

Databricks grew out of academia and the open-source world. It was founded in 2013 by the creators of the lakehouse architecture and key open-source projects including Apache Spark™, Delta Lake, MLflow, and Unity Catalog.

Who created Databricks?

Databricks was started by the original creators of Apache Spark, who were working at the University of California, Berkeley. The company was founded by Ali Ghodsi, Andy Konwinski, Ion Stoica, Matei Zaharia, Patrick Wendell, Reynold Xin, and Scott Shenker. Ali Ghodsi serves as CEO and has a background in both research and industry. The company provides a cloud-based platform for big data processing and machine learning.

Who is Databricks for?

Databricks serves a wide range of professionals working with data:

• Data Scientists
• Data Engineers
• Business Analysts
• Machine Learning Engineers
• Data Analysts
• Software Engineers
• DevOps Engineers
• Research Scientists
• Product Managers
• Statisticians

Getting started with Databricks

1. Create an account: Sign up on the Databricks website to access the platform.
2. Explore the interface: Get familiar with sections like “Training Overview,” “Databricks Academy,” and “Certification.”
3. Use training resources: Databricks offers curricula designed to help you build skills relevant to your needs.
4. Databricks Academy: Access the learning platform directly through the provided link.
5. Certification: Earn a Databricks certification to gain formal recognition of your skills.
6. University Alliance: For deeper involvement, the University Alliance section offers opportunities to teach Databricks yourself.