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.

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.

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.

This comprehensive guide delves into the essential features of Unity Catalog by Databricks, highlighting its role in enhancing security, automating data documentation, and streamlining ML and AI governance. Learn practical tips on integrating this powerful tool into your data strategy to boost productivity and ensure compliance. Whether you're scaling up or enhancing data discoverability, this article is your roadmap to leveraging data for innovation while maintaining robust security.

Inn this blog we address whether Unity Catalog can replace existing enterprise catalogs when integrated with Databricks. We clarify that while Unity Catalog excels at centralizing governance and enhancing data management within Databricks, it complements rather than replaces established catalogs like Alation or Collibra if they already add significant value.

With extensive experience in data solutions, our CEO Kai notes that Unity Catalog is indispensable for managing permissions and access across data, ML, and AI assets effectively. However, for broader governance needs, using it alongside other data catalogs ensures comprehensive management across all data systems.

Unity Catalog from Databricks is revolutionizing how businesses manage their data, providing a unified governance platform that centralizes control over data and AI assets. It enhances productivity, bolsters security, and streamlines compliance by offering a single, searchable repository for all data assets.

The platform automates data documentation with Generative AI, easing the workload on data stewards and enriching data management with semantic searches and interactive visualizations. Additionally, Unity Catalog's Lakehouse Federation integrates data across multiple platforms, ensuring seamless data accessibility. Its advanced data lineage capabilities offer clear visibility into data movements, crucial for compliance and informed decision-making, making it a strategic asset for any data-driven organization.

Building on our exploration of Generative AI applications, this article dives deeper. We'll uncover the technical details: what makes it work and what challenges it faces. This equips you to understand how projects are built, their hurdles, and the best practices to overcome them.

The democratization of AI birthed fantastic products, but also downsides. Information overload, a talent gap, and poorly executed projects highlight the need for "know-how." This article empowers you to navigate this new landscape.

For years, we've dreamed of having natural conversations with machines. Chatbots were our first attempt, but they relied on scripts and struggled with anything unexpected. Generative AI changes the game. It learns from massive datasets, creating responses on the fly and handling complex ideas. This summary focuses on text applications, but generative AI is making strides in image, video, and audio too. The future of AI is dynamic and full of possibilities.

Funny or not, building a secured, governed and scalable data platform that supports multiple types of use cases along with the data management processes and practices is very similar to building a skyscraper - the higher the building grows and supports more units and people, the complexity increases.

This guide will help you understand the complexities of Databricks, ensuring your data skyscraper stands tall and proud.