As a first-party Azure service, Azure Databricks has established itself as the leading Data + AI platform on Azure, enabling organizations to build scalable, enterprise-grade pipelines and AI-powered insights without vendor lock-in. After its best-in-class data warehouse engine broke the world record for performance in 2021, the platform has continued to advance, solidifying Azure Databricks as the premier place for Business Intelligence (BI) on Azure.
The same powerful Databricks SQL (DBSQL) engine that continues to break records is the central driver behind seamless integration with the entire enterprise BI suite. Below, we cover how teams can move faster and reduce complexity by streamlining integration with Azure services such as existing Power BI workloads or low-code Power Platform apps, and supplementing these BI workloads with AI-powered insights from native Azure Databricks capabilities.
Azure Databricks offers the most powerful data warehouse in the market. No-knob, auto-optimized DBSQL Serverless warehouses provide the fastest performance of any cloud data warehouse at the lowest price. Under the hood, AI-powered optimizations such as Intelligent Workload Management, Predictive Optimization, and Predictive I/O learn from your workloads to enable the highly-scalable warehouse to handle the largest datasets and maximize throughput, even at peak working hours.
DBSQL Serverless has gotten 5x faster in the past 3 years alone, and the improvements don’t stop there. The next generation of DBSQL was unveiled at this year’s Data & AI Summit. Thanks to continuous investment in performance, DBSQL Serverless now boasts 25% faster speeds out of the box, all without changing the price. Faster performance without the need to optimize your data layout, pre-calculate measures, or copy to external reporting layers means your dashboards are always up-to-date no matter what BI tool you use.
Building on top of the existing Power BI connector co-engineered with Microsoft, Azure Databricks has made things even simpler by offering a direct Publish to Power BI feature, allowing users to create Power BI datasets from Unity Catalog data directly in the Databricks UI. The process only requires a few clicks: select your data in Unity Catalog, choose your Power BI workspace, and publish. Within seconds, your dataset is available in Power BI Service for reporting and analysis. The feature supports all Power BI semantic model modes with the ability to choose Import, DirectQuery, or Dual mode table-by-table. Data models are entirely preserved, including relationships and metadata, which ensures consistency and saves significant time for BI teams.
Extending things further, Power BI semantic models can be automatically updated and refreshed using the Power BI task in Lakeflow Jobs. You can finally chain ingestion, transformation, and Power BI updates within a single pipeline, ensuring that Power BI models are always in sync with the latest data and avoiding costly scheduled refreshes. Changes are reflected immediately as they occur, without the need for piecing together custom API calls or relying on external orchestrators. The feature provides all of the observability and resiliency of Lakeflow Jobs and support is even coming soon for incremental refreshes.
Each of the methods listed in the previous section not only make things easier, but enhance Power BI datasets with Unity Catalog governance. This includes all of its detailed lineage, monitoring, and security offerings (including the ability to inherit fine-grained permissions and access controls). Outside of Power BI, Azure Databricks supports all enterprise BI tools, providing the only centralized data governance layer in the Azure ecosystem.
Azure Databricks takes things a step further by allowing you to define your semantic layer using Unity Catalog Metric Views. This feature allows you to define your business metrics once and consume them from any SQL client. No more conflicting metric definitions built by independent teams, or duplicated logic locked away in separate BI tools. Just consistent, reliable insights across the organization.
The new Azure Databricks connector for Power Platform enables seamless, real-time integration between Azure Databricks and Microsoft Power Platform, including Power Apps, Power Automate, and Copilot Studio. With this connector, organizations can build low-code applications and automate workflows that interact directly with a single copy of Unity Catalog data. The connector supports full read/write operations without the need for painful custom connectors, duplicated data, or complex maintenance. Once again, all access controls and governance in Unity Catalog are preserved, ensuring secure and compliant data usage across the Power Platform.
In addition to seamless integration with Microsoft tools, you can complement your existing BI stack with native Azure Databricks capabilities. Databricks One is a new workspace experience designed to help business users get the most out of data and AI with the least friction. It simplifies access to the Databricks suite of BI products, aptly named AI/BI because the same intelligence that powers the world’s best data science platform is now deeply embedded into its BI tools. Here we highlight the core experiences available in Azure Databricks – Dashboards and Genie.
AI/BI Dashboards allow you to quickly create AI-powered visuals within Azure Databricks and share them with anyone in the organization. Coupled with the remarkable performance of the DBSQL engine, consumers will always experience snappy and up-to-date dashboards, even for the largest datasets. Data analysts can use natural language to create visualizations, leverage integrated forecasting without any prior machine learning experience, and share dashboards with anyone in the organization.
But what truly sets Azure Databricks Dashboards apart is the integration with AI/BI Genie. Genie is an AI-powered assistant purpose-built for business users to interact with their data in natural language. By providing short instructions and example outputs, users with no SQL or dashboarding experience can get insights tailored to their unique business context.
To make things easier, Genie can be accessed directly within AI/BI Dashboards. Imagine an executive visits their favorite dashboard to check on important KPIs. Without leaving the dashboard, they can dig deeper into the underlying data, answer follow-up questions, and even summarize the visuals. A typical analysis that might have taken multiple days, people, or dashboards to complete can be performed in a fraction of the time by a single user with limited technical background. This is all thanks to the significant AI/BI innovations announced at Data & AI Summit, including Top Drivers analysis, Deep Research, and Knowledge Extraction.
Top Drivers analysis feature of AI/BI Dashboards.
Companies have been trying to add chat components to BI tools for years now with underwhelming results. Databricks has solved this problem by integrating your business’s semantics into AI/BI Genie. Now that these tools have a deep understanding of your data, it can provide answers that are relevant and consistent compared to legacy solutions. Genie’s APIs allow you to integrate with the Azure ecosystem to meet users where they are, unlocking multi-agent systems and popular interfaces such as Microsoft Teams. It’s never been easier to unleash productivity, simply by having a conversation with your data.
Azure Databricks is the most advanced, integrated, and governed platform for BI on Azure. The best data warehouse on the market powers a growing list of features such as direct publish to Power BI, a robust Power Platform connector, and industry-leading native capabilities in AI/BI Dashboards and Genie. Azure Databricks enables both technical and business users to build, automate, and scale BI solutions with unmatched speed, security, and flexibility. If you want to reduce costs, enable AI, and maximize productivity for your data and business analysts, Azure Databricks is the clear choice for BI on Azure.
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