Live briefing
Everything about Databricks
San Francisco-based software company
Databricks, Inc. is an American data software and artificial intelligence company headquartered in San Francisco, California. It was founded in 2013 by the original creators of Apache Spark, an open-source framework that was commercialized as Spark through the company. It offers cloud computing-based data analytics solutions, and can run on Amazon Web Services, Microsoft Azure, and Google Cloud Platform. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: DatabricksA 5-minute orientation
- Skim a recent paper: Comparing Cloud-Native MLOps Platforms: AWS, Azure, GCP, and DatabricksInfluential work since 2022
- Pick up a classic book: Azure Data Factory CookbookThe most-reprinted book on the subject
- Read the landmark paper: Phishing Detection Implementation using Databricks and Artificial IntelligenceCited 15 times
- Go sideways: Ali GhodsiA closely related topic
- Go sideways: ThoughtSpotA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Phishing Detection Implementation using Databricks and Artificial Intelligence
Federated Learning Implementation Framework using Databricks: Privacy-Preserving Model Training at Scale
Best Practices for Implementing Continuous Streaming with Azure Databricks
Real-Time Feature Engineering and Model Serving Architecture using Databricks Delta Live Tables
AutoML Pipeline Orchestration and Explainable AI Integration in Databricks Environments
Enhancing Corporate Finance Data Management Using Databricks And Snowflake
Operationalizing MLOps with Databricks Pipelines: Scalable Machine Learning in Cloud Environments
A Secure-by-Design Approach to Big Data Analytics Using Databricks and Format-Preserving Encryption
🆕 Influential since 2022
Comparing Cloud-Native MLOps Platforms: AWS, Azure, GCP, and Databricks
Gen AI For ELT (Extract, Load, Transfer) in Streaming Application with Databricks/Snow Flakes
Generative AI-Powered Framework for Scalable and Real-Time Data Quality Management in Databricks
Designing self-healing ETL pipelines with airflow and databricks
Building Scalable Data Lakes with Databricks and Snowflake: An Enterprise Approach
📚 Books worth reading
Azure Data Factory CookbookDmitry Anoshin, Dmitry Foshin · 2020- 📕Data Engineering with Databricks CookbookPulkit Chadha · 2024
- 📕Databricks Lakehouse Platform CookbookAlan L. Dennis · 2023
- 📕Optimizing Databricks WorkloadsAnirudh Kala, Anshul Bhatnagar · 2021
- 📕Azure Databricks CookbookPhani Raj, Vinod Jaiswal · 2021
- 📕Databricks Certified Associate Developer for Apache Spark Using PythonSaba Shah, Rod Waltermann · 2024
- 📕Building Modern Data Applications Using Databricks LakehouseWill Girten · 2024
- 📕Querying Databricks with Spark SQLAdam Aspin · 2023
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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