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---
title: Best databricks posts — August 2024 | daily.dev
description: The most upvoted databricks posts from August 2024, curated by the daily.dev community.
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og:description: The most upvoted databricks posts from August 2024, curated by the daily.dev community.
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# Best of databricks — August 2024

1. 1  
[](https://daily.dev/posts/data-ai-use-cases-from-the-world-s-leading-companies-1dbdurs06 "Data + AI Use Cases from the World’s Leading Companies")  
Article  
![Avatar of databricks](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/fa7aa720f2db4d1eba826814730482c8)databricks · 2y  
Data + AI Use Cases from the World’s Leading Companies  
Leading companies such as GM, McDonald’s, and Unilever are using Databricks to enhance business outcomes through data and AI applications. Examples include optimizing player mechanics for the Texas Rangers, reducing processing times for Minecraft, and powering autonomous tractors for Blue River Technology. Other notable use cases involve Ahold Delhaize USA's self-service data platform and Block's AI-powered infrastructure improvements.  
19
2. 2  
[](https://daily.dev/posts/an-introduction-to-time-series-forecasting-with-generative-ai-zzlfp5zes "An Introduction to Time Series Forecasting with Generative AI")  
Article  
![Avatar of databricks](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/fa7aa720f2db4d1eba826814730482c8)databricks · 2y  
An Introduction to Time Series Forecasting with Generative AI  
Time series forecasting is essential for business decisions and has traditionally faced accuracy limitations. Generative AI and time series transformers provide new capabilities for improved predictions by identifying patterns in vast datasets. Popular models such as Chronos, TimesFM, Moirai, and TimeGPT offer diverse features and configurations for different forecasting needs. Organizations can leverage these models within Databricks to enhance their forecasting processes, with available notebooks to facilitate the integration of these advanced tools.  
18
3. 3  
[](https://daily.dev/posts/supernovas-black-holes-and-streaming-data-inzdaepeq "Supernovas, Black Holes and Streaming Data")  
Article  
![Avatar of databricks](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/fa7aa720f2db4d1eba826814730482c8)databricks · 2y  
Supernovas, Black Holes and Streaming Data  
Learn how publicly available NASA satellite data on supernovas and black holes can be consumed and processed with Apache Kafka and Databricks. This guide covers the setup and use of Databricks Data Intelligence Platform, Delta Live Tables, and AI/BI Genie to simplify the ingestion, transformation, and visualization of streaming data. Detailed steps for using open-source Apache Spark and Kafka, along with Databricks enhancements for serverless compute and natural language querying, make this complex data accessible to data scientists and engineers.  
11
4. 4  
[](https://daily.dev/posts/accelerate-feature-engineering-with-photon-rctd2fdii "Accelerate Feature Engineering With Photon")  
Article  
![Avatar of databricks](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/fa7aa720f2db4d1eba826814730482c8)databricks · 2y  
Accelerate Feature Engineering With Photon  
Training high-quality machine learning models involves careful data preparation, which can be time-consuming for large datasets. The Photon Engine, now available in Databricks Machine Learning Runtime, significantly speeds up Spark SQL and Spark DataFrame workloads, achieving speed improvements of 2x-4x. The Photon Engine enhances ETL processes and feature engineering, especially for time series data, using a new point-in-time join implementation. Users can enable Photon in Databricks ML Runtime 15.2 and above for better query performance.  
10

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