The One-Minute-Manager view.
A 100M+ row store-operations table behind a dashboard that refreshed in about four hours. Rebuilt on the Lakehouse: sub-second cross-filter for thousands of concurrent Monday users, included in Athena services.
Data · Dashboards
Import existing BI dashboards and serve them sub-second to everyone
Athena reads existing report files, rebuilds measures and visuals on the Lakehouse, and serves sub-second cross-filters to thousands of viewers, included in Athena services.
Sub-second cross-filter on 100M+ rows · thousands of viewers · included in Athena services
- Report file
- PBIP
- JSON import
- Sub-second on 100M+ rows
- Viewer access included in Athena services
- Existing BI semantic model read and measures
- Lineage on every chart
The problem
Thousands wait while dashboards throttle and refresh
Capacity SKUs get bought and rationed. Refreshes take hours. Throttling hits on a third of days. The people who need the number are the last to get it, and the BI team spends its week defending a queue.
Meanwhile agents ask the same questions analysts do—hundreds of times per day—and throttled infrastructure cannot keep up. Throttled infrastructure and agents do not mix.
A dashboard is a question people ask together. It should answer at once.
How it works
Import, rebuild on Lakehouse, serve, trace
Import. Drop the Report file or export. Athena recreates measures, relationships, and standard visuals. Anything that did not round-trip is listed in the import report for you to rebuild once (typically exotic custom visuals; standard visuals, measures, and relationships import automatically).
Rebuild on the Lakehouse. Iceberg tables in your object storage; an engine that returns 2M-row scans in 79 ms and billion-row questions in milliseconds of engine time.
Serve. Publish as an Application. Viewers authenticate through SSO; access is included in Athena services. Each viewer sees data with their own warehouse permissions.
Trace. Every chart carries lineage: source table, transformation, freshness. Time-travel compares this week's dashboard to last week's.
People and agents
What people and agents each do
Dashboards. Import existing BI reports as they are. Fast filters, viewer access included in Athena services, and each person sees only their own slice. 79 ms on 2M rows in testing.
| Capability | People can | Agents can | Together |
|---|---|---|---|
| Dashboards | Open, filter, and share; build new views. | Answer questions against the dashboard and link to it. | The number an agent quotes is the number on the dashboard. |
Anything a person can do here, an agent can do with the same permissions, and both land in the same audit trail.
Use cases
Consolidating six capacities into one.
Seven ungoverned BI capacities, each with its own refresh schedule, throttling, and license pool. One governed Lakehouse platform; one refresh schedule; viewer access included in Athena services.
Explore, with your styling intact.
Generative charts and cross-filters. Saved explorations. User-owned style overrides survive agent rewrites: when Athena rebuilds the chart, your color and formatting choices stay.
Time travel.
Compare a dashboard to itself as of a week ago. See what moved and why.
Legacy BI plus.
Not ready to move? Athena reads the existing BI semantic model, runs its measures, and browses reports from the same surface your agents use. Start there.
Distribution without seats.
Publish as an Application. Provision by SSO group. A wholesaler app gives each partner only its rows.
What customers say
“One workspace. All different, let's say, avatars of their output data. Right? Suddenly, it's dashboard. Excel is here. PowerPoint is when it's all together. It's very impressive.”
“I think a good replacement for the BI. Correct? I don't really need a BI help here. I can develop my own dashboards.”
“It's good to understand the capability of the platform. That how far, and how quickly you guys can get these things going [...] that has been impressive overall.”
“Lets us get a lot more out of our data than [...] We can sit on top of all of the data in [our data warehouse] as opposed to just, like, our little ingested, you know, three gigabytes semantic models. I think we have a lot of power here.”
“Gave Athena the spreadsheet, explained which column I was trying to figure out, and then ten secs it told me... exactly how the calculation was based on the other data.”
“He wrote the entire stuff. By itself. And I was there, and I was thinking, alright. If I had to write all this stuff, I mean, I would've spent days, days, days.”
“Use the Athena platform probably closer to the concept and how it was designed, like, with the spaces architecture where you've got a set of primitives and capabilities, and you bring together the right set of capabilities to solve a task.”
“Digital worker, it gets spun up, it gets given access to the toolkits that it needs. It gets given access to the data that it needs. Just exists for the period it needs to exist to perform the task. And then it gets torn back down again afterwards.”
“I like that direction, that concept of the agent is the agent. It becomes an entity in its own right with its own ownership and its own missioning, and you get rid of the gray area and the blurry lines.”
“It was PowerPoint... there was no kind of distinction between the two. So that was killer. And I literally had a meeting on it today, and people said how great it was.”
Verbatim from customer calls. Customers anonymized.
Coexistence
Read semantic layers before you rebuild
If you have real spend on BI, warehouse, or lakehouse tools, we want that business. The path is: read the semantic layer today, rebuild one throttled dashboard, move tables when the cost case is clear. Consolidation is the outcome, not the demand.
Governance
Security and governance
Viewers see data with their own warehouse permissions, inherited live.
Dashboards are assets: owner, versions, lineage, citations.
Deploy with the platform: managed cloud, your VPC, on-prem, air-gapped.
Every agent-made change to a dashboard is attributed and reversible.
What to plan for
Exotic custom BI visuals do not always round-trip. Standard visuals, measures, and relationships do. The import lists what did not; you rebuild those once.
FAQ
Why build dashboards on Athena?
They are fast for everyone at once, built on governed definitions, and people can ask the agent questions about what they see.
Can we bring our existing reports?
Yes. Import them and move them one at a time.
Who can view them?
Anyone you grant access to; viewer access is included in Athena services.
One platform underneath
AGS · Athena Governance System
Records every change by a person or an agent, rolls back one contributor's edits without losing anyone else's, and keeps the model, instructions, and sources behind each agent action.
Palladium · deployment
How the platform is deployed: Athena's managed cloud, your cloud on AWS, GCP, or Azure, on-prem, air-gapped, or GovCloud. Same platform in every option.
How it fits together
Build, Work, and Data on top; 150+ connectors and every surface in and out; one map of the whole platform.
The rest of the platform
Related products and stories
Bring your slowest dashboard.
We will import it, rebuild it, and let you click the filter.