Learn how Databricks metrics views simplify SQL analytics by centralizing business rules and eliminating repetitive code. Complete tutorial with examples.

Bridge the gap in your data architecture by strategically combining Databricks BI/AI with traditional business intelligence tools. Learn how to reduce licensing costs, improve dashboard performance, and implement a hybrid approach that leverages the best of both worlds. This practical guide shows you when to use native Databricks capabilities versus tools like Power BI for optimal cost-efficiency and performance.

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.

Learn how to integrate SAP data into Databricks with this comprehensive blog. Discover the essential components of the SAP ecosystem, including SAP HANA, S/4HANA, and BTP, and explore proven integration methods using SparkJDBC and Azure Data Factory. Perfect for data engineers and architects looking to combine SAP's enterprise management capabilities with Databricks' advanced analytics.

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.

This guide dives into the technical steps required to migrate from Amazon Redshift to Databricks. Covering everything from discovery and data evaluation to security protocols and cost estimation, it offers detailed, practical strategies for managing dependencies, optimizing queries, and planning for future scalability within Databricks’ robust ecosystem.

This blog introduces the strategic benefits and challenges of migrating from Amazon Redshift to Databricks. It covers Redshift’s legacy limitations, Databricks' advantages, and critical migration factors. The article provides an overview of key planning steps, including architecture considerations and phased migration strategies, setting the stage for technical execution in the upcoming part two.

Sigma offers a user-friendly BI tool ideal for building and managing dashboards. With intuitive features, seamless embedding, and live data connections, it excels in usability. However, its steep pricing and lack of Git integration may deter small businesses. SunnyData recommends Sigma for startups and enterprises seeking responsive, customizable solutions.

This blog explores the migration process of Databricks from one cloud provider (GCP) to another (Azure or AWS). It emphasizes using tools like Terraform for seamless migration, best practices for handling resources, data, and configurations, and discusses strategic reasons for switching cloud platforms.

Databricks vs. Snowflake vs. Fabric evaluates key aspects like toolsets, partner ecosystems, flexibility, ease of use, and overall business value. We break down each platform's strengths and weaknesses to guide you in choosing the best for your data strategy.

Databricks is a top choice for startups seeking an all-in-one data platform for analytics, AI, and data management. Its cloud-native, scalable, and cost-efficient architecture allows startups to begin small, grow, and avoid complex migrations as needs evolve.

In this blog, we outline the essential steps for migrating ETL workloads and EDW from Snowflake to Databricks. From data migration to report modernization, we break down five key phases for a seamless and efficient transition to Databricks.

This blog explores why companies are increasingly migrating from Snowflake to Databricks, highlighting Databricks’ integrated platform, cost-efficiency, and comprehensive data and AI capabilities. The post examines the pitfalls of Snowflake's pricing and its struggle to replicate Databricks' functionality.

This blog compares Microsoft Fabric and Databricks, focusing on pricing, features, governance, and scalability. It concludes that while Fabric suits smaller businesses, Databricks excels for medium to large enterprises due to its flexibility, innovation, and advanced data capabilities.