AI/BI Dashboards
Recent items mentioning AI/BI Dashboards across the Databricks ecosystem — releases, news, videos, and community Q&A. Updated hourly.
Practitioners are hitting gaps in AI/BI Dashboards tooling: a community thread asks how to link a bundle-managed Genie space to an AI/BI dashboard across environments with Asset Bundles 1, and another asks how to measure a dataset's row count and size inside a dashboard 3. A Reddit thread questions whether Lakeview lacks basic functionality 2. Separately, a Reddit post shows an expense management app built with the Genie App Builder on Lakebase, using AI for image scanning 4.
Generated daily from the 4 most recent items mentioning AI/BI Dashboards. Click any [N] to jump to the source.
Asset Bundles: how to link a bundle-managed Genie space to an AI/BI dashboard across environments (o
Lakeview missing basic functionality?
Hopefully someone can help point me in the right direction or offer workarounds, but it seems like Lakeview dashboards are missing super basic functionality. Specifically two things: The ability to click to filter a table via a given field on the table header, similar to an Excel filter. It’s not possible to add widget filters for every single possible combination of things users may want to filter based on. Am I missing something? Is there a custom viz option that delivers this? The ability to sort a pivot table via the UI. I can define a sort criteria for the table, but what if my users want to sort by something else? Again, this seems pretty basic - maybe I sort by total revenue but then users want to sort or filter for a given contract ID, meaning I need to take up dashboard space with another widget. Lakeview is solid in a lot of ways, especially building via AI, but I don’t understand how it’s missing these super basic things, especially click to filter. I’m trying to hack my way around it with a custom filter but that gets pretty complicated fast and doesn’t deliver a great UX. submitted by /u/GiraffesRBro94 [link] [comments]
How to measure a Dataset row count and size in AI/BI Dashboards?
Building an Expense Management App with the Genie App Builder Leveraging Lakebase + AI for Image Scanning
I previously did not consider Databricks a great place to build apps on with AI. With the release of Genie App Builder (still in beta), that has changed, and now I see it as a serious player in the AI app building space. Before I start, quick disclaimer: I am part of the Databricks MVPs, work for a consulting company that is a Databricks partner, etc. That said, this review is fully based on my experience, my own words, my own testing, etc. Always try things out yourself! Things I appreciated: +By far, this feels like the most polished Databricks beta that has been released. If the goal is to make this easy for business users to develop applications easily and securely, this feels like it is already there. Granted, I have not tested with multi-users yet, but it feels very polished already. +Native integration with Databricks features like Lakebase. +Even though it has native integrations to Databricks features, it didn't force these features in building what I did when it was otherwise unnecessary. For example, the dashboard it built as part of the application was not an AI/BI Dashboard. I would have expected it do that, but it didn't, and rightfully so, as it would not have been truly the best thing for this use case, so truly a customer first thing here. +Respects governances/access controls, meaning I can develop an application freely in the sandbox environment, but if I want to deploy it, organizational safeguards, Unity Catalog, and other controls built on Databricks apply. Things that could be better: -With the goal of empowering citizen devs (or i should just say, business users that are technical enough), there needs to be an easier way to send request for access/capability etc to admins. Right now, the builder tells you through the chat, but that is not as intuitive as having a clear UI-embedded to-do things before deploying etc. One step further would be that the developer can notify the administrator of this need. -I found that when I developed an application that had to use a sandbox only capability when access was otherwise unavailable (see above), just hung when I tried to reopen the dev experience for it. I had to troubleshoot through the chat interface as to why that was happening to figure this out. Additional Note : Currently free at the moment, but pricing is not yet available since we are in beta. Will be interesting to see how the overall value of this capabilities plays out factoring the ease & governance vs compute & token costs. Closing Thoughts I think this is on track to be one of Databricks' best released feature, and a serious entry in the space that is otherwise feel with undifferentiated app building solutions. Is it creating a new category? No. But it feels like an Apple-level product, where being the best at executing is sometimes better than being the first to do something. And I believe it will pay off as businesses look more carefully as to where they spend their hard-earned money on. From a "data + AI platform vendor" perspective, this is currently the best offering of its kind. From an "app building vendor" perspective, there are still solid players out there, but for enterprise focused apps, in the top 3 of options I would consider, and for sure the first one I would try if my stack was heavily Databricks focused. submitted by /u/JosueBogran [link] [comments]
💡 NEW: Create Relationships in Databricks AI/BI Dashboard
Is Databricks Replacing Power BI and Tableau in the Enterprise?
Why did Databricks get into the BI tooling space & what does it mean for Databricks customers using Power BI, Tableau, and other established BI tools? In this 3-min video, David Meyer (SVP @ Databicks) shares how Databricks can help both provide advance decision making capabilities and lower costs, as well as where some of the older tools fit in your stack. This was recorded in front of a live audience at the Databricks Data + AI Summit 2026. Hope you enjoy it, and would personally love to hear your stories, both where AI/BI Dashboards from Databricks has been able to take on more of your BI workloads, as well where you still find gaps that need to be addressed! submitted by /u/JosueBogran [link] [comments]
Dynamic chart titles in Databricks AI/BI
A good dashboard design practice is to always make it clear what the user is looking at by providing context for each metric. Databricks AI/BI dashboards make that easier with a simple but useful feature: you can now referencse filters and fields directly in visualization titles and descriptions using @. For example, instead of a generic title like: - Revenue by Region you can make it dynamic by referencing field - Revenue for \@region Now when someone changes the filter, the title changes with it. When a dashboard has several filters and interactions, it’s surprisingly easy to lose track of the context behind a number or chart. Having that context reflected directly in the visualization makes the dashboard feel much more intuitive. https://reddit.com/link/1wn02wy/video/gavm1gcp60rh1/player submitted by /u/szymon_dybczak [link] [comments]
5 Ways to Enhance Databricks AI/BI Dashboard Tables with HTML
Built a Databricks medallion pipeline for NYC Taxi data
Been working on this as a way to get hands-on with Databricks Asset Bundles and Unity Catalog governance. It's a migration of an old on-prem NYC Taxi analytics stack (ClickHouse + Spark + Docker + Terraform) into a proper Bronze/Silver/Gold lakehouse. A few things I focused on: Auto Loader for incremental ingestion, triggered by file arrival Data quality handling that doesn't just drop bad rows — duplicates, zero-distance trips, and reversed fares go into dedicated quarantine tables instead of being silently discarded Databricks Asset Bundles for deploy/orchestration (dev + prod targets) 3 published AI/BI dashboards on top of the Gold layer (fleet ops, finance, compliance) It's intentionally small in scope — meant to demonstrate the lakehouse pattern, not be a production-scale platform. Currently only Green Taxi data; FHV comparison is planned next. Repo: https://github.com/Hamza-Bouali/NYC-DATABRICKS Would love feedback, especially on the Silver-layer data quality rules or the bundle structure open to critique. https://preview.redd.it/ej6hvzrbokph1.png?width=1667&format=png&auto=webp&s=b090b2c5165efcc83fb3f2b5c38ff6ef34c8ef48 https://preview.redd.it/rih9a5sbokph1.png?width=1879&format=png&auto=webp&s=1b85b90608e1b1273da4f8cbb4fa65d9f2c397a7 https://preview.redd.it/kjdor4sbokph1.png?width=1687&format=png&auto=webp&s=677c6194ede0cd01a8630ee98f85d11a5146b410 submitted by /u/No-Pollution-2274 [link] [comments]
Community BrickTalk | Real-Time Data & AI: Tripwise Demo
Hey r/Databricks ! Join us for community BrickTalk on Thursday, September 24 , focusing on real-time data streaming, AI agents, and governance using Databricks. BrickTalks is a community event series where Databricks experts share real-world use cases, demos, and practical insights for building with Data and AI, giving customers a direct line to the people behind the products. In this session, we'll walk through a live demonstration of the Tripwise Demo , featuring: Sub-Second Transactions & Streaming: Device registration into Lakebase with sub-second reads/writes, plus telemetry streaming via Zerobus through a governed Medallion architecture. AI-Generated Offers & Pricing: Generating real-time agent offers using Foundation Model APIs and scoring behavioral data for usage-based renewal pricing. Natural Language Analytics: Enabling underwriters, product managers, and marketing teams to query governed insurance data in seconds using AI/BI Dashboards and Genie. Unified Governance: Managing safety, compliance, and control end-to-end with Unity Catalog. This is a great chance to see real-world architecture in action and ask questions directly to Databricks experts. When: Thursday, September 24 9:00 AM PT 12:00 PM ET 5:00 PM BST (London) 9:30 PM IST Register here and save your spot submitted by /u/Subject_Ant1789 [link] [comments]
CSV export from AI/BI Dashboard table widget does not preserve visual column order
Beyond embedding: How to secure AI/BI Dashboards for every viewer
A single AI/BI dashboard can now serve every viewer securely: one entitlements table plus the signed embed token's __aibi_external_value control row-level access per viewer, so teams avoid duplicating dashboards or repeating filters across queries. Access is driven by identity-provider group membership rather than manually maintained user lists, and the pattern layers default-deny protections—masked columns, refused tokens for unentitled viewers, and Unity Catalog row filters—for defense in depth.
AI/BI Dashboards
Custom Visualizations in Databricks AI/BI Dashboards: Build a Dumbbell Chart
Moving ~150 Tableau dashboards to Databricks AI/BI - anyone done this at scale?
We are considering moving from Tableau to Databricks AI/BI Dashboards and wanted to see if anyone here has made a similar move. We currently have around 150 Tableau dashboards used by 1,000+ users, with a mix of technical and non-technical users. Most of the underlying data already lives in Delta tables, so naturally we're looking at whether it makes sense to consolidate and use Databricks for the dashboarding layer as well. For those who have done this, how has the experience been? Anything you wish you knew before migrating? Any major limitations compared to Tableau, especially around visualization, performance, or the experience for non-technical users? I'm also curious about cost at scale. With 1,000+ users potentially hitting dashboards, did SQL warehouse usage become a concern? Would you feel comfortable replacing Tableau completely with AI/BI Dashboards today, or do you still find yourself needing Tableau for certain use cases? Would really appreciate hearing about real-world experiences. submitted by /u/Immediate_Bus5250 [link] [comments]
Attach files in Genie Code
Genie Code is getting a new feature 🥳 Good news you can attach a document to Genie Code when you need it as temporary context for the current conversation. What's a good use case? 🔴 Explain or summarize a document: “Summarize this PDF and list the key decisions.” 🔴 Extract information from PDFs, scans, or images. 🔴 Generate code based on a specification: attach a requirements document and ask Genie Code to create Python or SQL. 🔴 Analyze data files such as CSV, Excel, JSON, or JSONL. 🔴 Convert documentation into code, tests, or a notebook. 🔴 Interpret diagrams, charts, architecture sketches, or screenshots. 🔴 Migrate Tableau or Power BI files into AI/BI dashboards using /importBI. What are the supported file types ? .pdf, .csv, .xlsx, .xls, .json, .jsonl, and common image formats. submitted by /u/Youssef_Mrini [link] [comments]
How to remove/delete a Relationship Graph (Semantic Model) from an AI/BI Dashboard?
AI/BI Dashboard pivot export: Excel
Custom Visualizations in AI/BI Dashboards: Build a Pareto Chart with Vega-Lite
How to export clean values from ai/bi dashboard table that uses html formatted columns
Building Plug-ins for AI/BI Dashboard
How to limit the AI/BI dashboard sharing people-picker to workspace members
NewsGenie Code Skills: Maintaining Quality at Scale
Genie Code can automatically generate a Databricks AI/BI dashboard from a simple business prompt, performing data discovery and dashboard authoring. By adding a "skill" to Genie Code, users can enforce engineering standards like bronze, silver, and gold table creation, dimensional modeling, and automated refresh jobs, making the output production-ready and repeatable.
AI/BI Dashboard Navigation: Nested Tabs, Page Structure, and Reusable Visuals
Geospatial Unbounded: Spatial SQL GA with AI/BI Maps, Delta Sharing, and Iceberg v3
Spatial SQL is now Generally Available on Databricks, bringing native geospatial data types, 90+ ST_* functions, and AI/BI Dashboards that render maps natively. This release also includes major performance improvements, open lakehouse support via Delta Sharing and Iceberg v3, and Apache Spark 4.2 compatibility for geo columns.
Metric Views in AI/BI Dashboards & Genie (Part 2 of 3)
I Finally Get Why Everyone's Excited About Databricks AI/BI Dashboards
The SDK now supports more granular AI agent detection in User-Agent headers and passes unrecognized values as-is. Several API changes introduce new fields for dashboards, apps, ML materialized features, and synced table statuses, along with a Revert method for Lakeview dashboards.
This release introduces new methods for Lakeview and Postgres services, including revert() for Lakeview and undeleteBranch() for Postgres, along with new fields across various services like Jobs and IAM. Several breaking changes require actionType and resourceId for bundle operations, cliVersion for bundle versions, and alter the tags field for Marketplace listings and pagination for cluster events.
This release introduces the new bundle package and workspace-level service, alongside a revert method for Lakeview dashboards and an undelete branch method for Postgres services. Breaking changes include modified pagination for the cluster events API and a type change for the marketplace listings request tags field to a dedicated dataclass.
Reports migration made easy through genie Code!
Genie Code now supports migrating from Tableau and PowerBI. With the new /𝒊𝒎𝒑𝒐𝒓𝒕𝑩𝑰 command, you can: → Upload a .twb, .twbx, .tds, .tdsx, or .pbit file directly → Auto-generate an AI/BI dashboard that mirrors your existing visualizations → Convert measures & dimensions into reusable metric views → Promote them to Unity Catalog for governance, lineage, and access control The migration path that used to take weeks now starts with a single command.
Databricks now supports importing Tableau and Power BI files into Genie Code to automatically build AI/BI Dashboards with Metric Views
With **Genie Code**, you can now add a Tableau or Power BI file and have it build an **AI/BI dashboard** that replicates your existing visualizations - while connecting them to **metric views** that mirror the underlying business logic. [Import BI files using Genie Code - Azure Databricks | Microsoft Learn](https://learn.microsoft.com/en-us/azure/databricks/dashboards/manage/import-bi#requirements) Many organizations have years of BI logic embedded inside workbooks, reports, templates, and semantic layers. Rebuilding that logic manually in a new platform can be slow, error-prone, and difficult to govern. This new workflow helps accelerate that migration path: 1. Upload a Tableau or Power BI file directly into Genie Code Supported formats include `.twb`, `.twbx`, `.tds`, `.tdsx`, and `.pbit`. 2. Use the `/importBI` command in Agent mode Genie Code imports the BI asset and generates an AI/BI dashboard. 3. Review the generated dashboard and metric views Measures and dimensions from the original file are transformed into metric views. 4. Promote metric views to Unity Catalog This makes them reusable across dashboards, Genie Spaces, and notebooks, while adding governance, lineage, access controls, and discoverability. Currently, there is also a 100 MB limit for direct file uploads. For larger files, the recommended path is to store the file in a Unity Catalog volume and reference it directly, for example: `/importBI @/Volumes/my_catalog/my_schema/my_volume/sales_workbook.twb`
The Top 10 Best Practices for AI/BI Dashboards Performance Optimization (Part 2)
The Top 10 Best Practices for AI/BI Dashboards Performance Optimization (Part 1)
NewsApache Iceberg V3 on Databricks: From Ingestion to Analytics
The video demonstrates Apache Iceberg v3 on Databricks, showcasing how its new variant column type natively handles semi-structured data and how row-level concurrency enables simultaneous data ingestion and corrections. It also highlights cross-platform data accessibility from open-source Spark via the Iceberg REST catalog, ensuring no vendor lock-in.
How to programatically extract rendered or computed data from AIBI Lakeview dashboard widget via API
The question your commercial data should already be able to answer
Databricks and Veeva now embed Genie AI agents and AI/BI dashboards directly into Veeva Vault CRM, enabling life sciences commercial teams to get real-time answers to their questions without leaving their workflow. This unified Databricks lakehouse with Unity Catalog delivers governed commercial data to every persona, from sales reps to MSLs, in the format and depth their role requires.
NewsStop Guessing Table Health — Let These Dashboards Tell You
Databricks offers two dashboards for monitoring table health and access: the Table Access Advisor and the Table Health Advisor. These dashboards provide insights into table ownership, read/write patterns, staleness, optimization status, and underlying file structures, helping users identify ghost tables and ensure best practices.
TutorialsFrom Excel to AI Agents: The Evolution of BI Explained
The video explains the evolution of Business Intelligence (BI) through four phases, from IT-centric to analyst-driven, then semantic layers, and finally to a future where AI agents are primary BI users. It demonstrates how Databricks' BI stack, including Dashboards, Genie (natural language interface), Metric Views (semantic layer), and Databricks One (serving layer), addresses these evolving needs by providing a unified, open, and AI-ready platform.
NewsNever Build a Dashboard by Hand Again
The Databricks assistant, now called Genie code, can automatically generate multi-page dashboards from a blank canvas using natural language prompts. Users define a metric view as the data source and then describe desired dashboard pages, visuals, and themes, with Genie code planning and executing the build.
TutorialsDatabricks AI Dev Kit Demo - Install, DataGen, SDP, Dashboard
The video demonstrates installing the Databricks AI Dev Kit on a Mac, then uses it to generate synthetic data, create serverless Spark declarative pipelines for a medallion architecture, and build a Databricks dashboard based on the generated data. It highlights how the AI Dev Kit leverages skills and an MCP server to automate these development tasks.
This release introduces new resources for managing Postgres databases, data classification catalog configurations, and knowledge assistant features. It also renames the databricks_apps_space resource to databricks_app_space.
TutorialsDatabricks End-To-End Project | Zero-To-Expert | Streaming, AI, Lakeflow, Unity Catalog, AI/BI
This video demonstrates building an end-to-end restaurant analytics platform on Databricks, covering streaming and batch data ingestion, AI-powered sentiment analysis, and dashboard creation. It teaches how to use Unity Catalog, Lake Flow Connect for CDC, Spark declarative pipelines for real-time data from Event Hub, and how to construct a medallion architecture with fact and dimension tables.
TutorialsUnity Catalog Metric Views - Why you should care about Databricks' new Semantic Models
Unity Catalog Metric Views are Databricks' new semantic models, allowing users to define business-friendly names, dimensions, and context-sensitive measures for data. These views centralize KPI definitions, enabling consistent use across dashboards, AI tools, and downstream BI platforms, and are created using YAML.
The assessment workflow now includes a force-refresh parameter to rerun assessments and obtain updated results, and a new experimental workflow converts Azure WASBS URLs to the more performant ABFSS format. Dashboard management is now more resilient, automatically recreating dashboards when permission issues occur or they're trashed, and service principals are now supported as members of account groups.
NewsAI/BI Dashboards - July 2025 Updates
Databricks AI BI dashboards have added several new features, including custom dashboard themes, global filters, drill-through capabilities, and file uploads. The updates also introduce automated forecasting, chloropleth map visualizations, and scheduled parameterized reports.
Tutorials46 AIBI Dashboards & Visualizations | Consumer Access in Databricks | Forecasting Reports
AIBI dashboards in Databricks enable users to create interactive visualizations and reports from their data using a drag-and-drop interface, with AI-assisted features like automated visualization generation and forecasting. Business users can then access and consume these published dashboards through a simplified consumer access profile that restricts permissions to viewing and refreshing only.
TutorialsHealthcare Interoperability: End-to-End Streaming FHIR Pipelines With Databricks & Redox
Redox streams healthcare data from EHR systems into Databricks by converting various formats (HL7, XML, X12) to FHIR JSON with normalization and connectivity handling. Databricks processes FHIR data using SQL and AI without specialized software, enabling real-time analytics and bidirectional data exchange for healthcare use cases like prior authorization.
NewsData Triggers and Advanced Control Flow With Lakeflow Jobs
Databricks Lakeflow Jobs includes data triggers that automatically run pipelines when files arrive or tables update, ensuring jobs execute only when data is ready. Control flow features like for-each loops, conditionals, and repair-run enable building complex, modular pipelines with reduced costs and simpler debugging.
UCX v0.58.0 adds offline installation support for restricted-access environments and enables creation of account-level groups from nested workspace groups for improved governance. The release also enhances dashboard navigation with hyperlinks to table and cluster resources, and includes fixes for assessment exporters and improved error handling in the Workflow linter.
This release adds Databricks Runtime 16+ support, fixes cluster policies on UC-enabled workspaces, introduces HMS Federation Glue credential migration, and refactors pipeline migration from skip-pipeline-ids to include-pipeline-ids. The migration progress workflow now runs automatically daily at 5 AM UTC while improving dashboard migration tracking and Python error reporting.
NewsKen Wong, Sr. Director of Product Management at Databricks on Bringing AI to Business Intelligence
Databricks launched Lakeview AI, a business intelligence platform that combines traditional no-code dashboarding with a conversational AI assistant called Genie. The system uses compound AI models and metadata integration to answer natural language queries, learn business-specific semantics from user interactions, and handle complex data contexts.
NewsDatabricks SQL: Why the Best Serverless Data Warehouse is a Lakehouse
Databricks SQL is a serverless data warehouse built on the lake house architecture that unifies business intelligence and AI workloads. The video discusses the platform's core capabilities, including streaming tables, materialized views, workflows, intelligent workload management, and upcoming features like the Lakeview dashboarding experience.
TutorialsWhat's New in Databricks SQL -- With Live Demos
The Databricks SQL presentation demonstrates new features across data ingestion, governance, transformation, management, and business intelligence integrations. The video provides live walkthroughs of streaming tables, query federation, materialized views, Python UDFs, AI assistance, Lakeview dashboards, and enhanced system table monitoring.