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.

There is a lot of buzz around GenAI, LLMs, AI, and ML. Knowing what you should implement or not implement is tough.
In this set of 3 videos, our Technical Advisor Josue Bogran has a frank and open conversation about these subjects with Denny Lee, Principal Developer Advocate at Databricks.

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.

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.

Migrating to Databricks offers companies unmatched benefits, including cost efficiency, scalability, and advanced AI/ML capabilities. With a unified platform and robust data governance, Databricks empowers businesses to modernize their data estates, ensuring they’re future-ready and positioned for growth.

This blog argues against the rush to adopt the latest AI technologies, emphasizing the importance of strong data engineering foundations and "Classic Analytics." It advocates for a balanced, pragmatic approach to AI adoption, ensuring long-term success over short-term gains.

Databricks AI/BI Genie leverages advanced AI models and Unity Catalog to answer business-specific queries with precision. This blog explores its potential to surpass traditional dashboards, offering a powerful tool for real-time, self-service analytics in a governed environment.

This article provides an initial analysis of Microsoft Fabric, comparing it with Databricks. It discusses why Fabric may not meet enterprise needs and explores potential integrations between Fabric and Databricks, highlighting how they can complement each other in data projects.

Databricks' AI Assistant is now GA and excels in SQL tasks, leveraging Unity Catalog metadata. It consistently delivers functional SQL queries and follows instructions well, proving itself superior to alternatives like ChatGPT for SQL code generation. Watch the video for insights.

The Data Mesh approach decentralizes data management to empower business units, facilitating quicker and informed decision-making. While promising for large institutions with mature data strategies, it presents challenges such as complexity, data fragmentation, and loss of economies of scale. SunnyData offers insights into whether Data Mesh is suitable for your organization.

Databricks' latest notebook upgrade offers superior design and performance, versatile language support, and improved user experience, making it a standout product for data analysis and exploration.

Databricks is making strides in AI/BI Dashboards with enhanced data prep and intuitive UI. Discover its pros, cons, and future potential 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.

Here we present Databricks Summit 2024 18 biggest announcements, including Generative AI tools, AI-powered BI dashboards, open-source Unity Catalog, no-code data ingestion, serverless compute, secure data collaboration, built-in AI functions for data warehousing, and the all-new Delta Lake 4.0. Discover how these advancements can unlock the full potential of your data. Get the details and see how SunnyData can help - read now!

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.