Configure Databricks compute policies to prevent accidental overspending. Step-by-step guide to setting auto-termination, worker limits, and access controls that protect your budget without limiting productivity.

How 7 Databricks accelerators are helping banks and financial institutions replace expensive vendor solutions with custom in-house data applications for AML, fraud detection, customer analytics, and compliance.

CI/CD pipelines can pass all jobs yet still deploy broken functionality. This blog covers smoke testing, regression testing, and critical validation strategies: especially useful for data projects where data quality is as important as code quality.

Most Databricks cost comparisons focus only on compute pricing, missing two critical factors that can save thousands monthly. Learn how serverless waives private link transfer fees (up to $10/TB) and provides persistent remote caching that survives warehouse restarts - hidden benefits that often justify the serverless premium entirely.

Discover how data fragmentation across multiple platforms creates costly silos and slows decision-making. Learn why Databricks offers the unified solution modern enterprises need.

In this three-part video series, Databricks MVP Josue Bogran and Greg Kroleski from Databricks’ “Money Team” discuss cost allocation, tagging best practices, cloud innovations, and performance enhancements. The series explores Databricks' efforts to optimize cost reporting, leverage AI for insights, and empower businesses to make smarter, growth-driven decisions in 2024 and beyond.

Discover why Databricks stands out as the leading data platform in this insightful blog. From unified data management to cost efficiency, unmatched performance, and robust analytics, Josue Bogran explains the top 5 reasons Databricks excels in the competitive landscape. Learn how Databricks balances innovation, user-centric design, and industry versatility to deliver exceptional results.

Josue Bogran interviews Jeremy Lewallen from Databricks’ Performance Team, exploring benchmarks, storage cost optimization, rightsizing SQL Serverless Compute, and common compute mistakes. Discover why Databricks continually enhances performance, tips for using the latest DBRs, and how their innovations provide a fast, efficient, and developer-friendly data platform.

Transitioning to Databricks reduced costs by $19K/month and streamlined data operations. Learn how Databricks' unified platform simplifies data engineering and boosts efficiency in our latest blog.

Evaluating Databricks' cost control features reveals strengths in granular tracking and user-friendly budgeting, but highlights areas for improvement in automated alerts and comprehensive expense tracking. Explore our insights on Databricks' budgeting tools.

Discover how to manage pipeline costs effectively with Databricks Workflows. This article offers practical tips to reduce total cost of ownership without sacrificing performance, and provides insights into understanding your costs better. Learn strategies like using job compute and spot instances, setting warnings and timeouts, leveraging task dependencies, and implementing autoscaling and tagging. Optimize your resource usage and get the most out of your Databricks environment. Read on for actionable advice to streamline your data processes.

Disappointed by the high failure rate of AI initiatives? You're not alone. This post unveils the secrets to planning and executing a successful AI project. We detail our proven methodology for ensuring AI success, focusing on identifying high-ROI use cases and navigating the Proof-of-Concept stage effectively. Learn how to choose the right supplier, avoid common pitfalls, and ensure your AI project transitions smoothly from pilot to production, delivering real business results and a competitive edge.

In the evolving world of AI and ML, businesses demand efficient, secure ways to deploy and manage AI models. Databricks Model Serving offers a unified solution, enhancing security and streamlining integration. This platform ensures low-latency, scalable model deployment via a REST API, perfectly suited for web and client applications. It smartly scales to demand, using serverless computing to cut costs and improve response times, providing an effective, economical framework for enterprises navigating the complexities of AI model management.

Photon, a C++ native vectorized engine, boosts query performance by optimizing SQL and Spark queries. It aims to speed up SQL workloads and cut costs. This blog will help you understand Photon's role in enhancing Databricks, ensuring you grasp its significance by the end.