Rippling Data Cloud: BI and Dashboards

As part of today's Rippling Data Cloud announcement, we launched Business Intelligence (BI) and Dashboarding that connects your operational data to your people data to unlock new analytical capabilities. Let's take a look at what makes BI and Dashboards unique inside Rippling.

What is it?

Rippling BI and Dashboards are the analytical charting and dashboarding capabilities that allow users to visualize data that is available to Rippling, either because it originated there, is accessible via Zero Copy, or was imported using Rippling Data Connectors and Transformations. It also includes Rippling AI’s ability to autonomously design and render Dashboards based on your questions.

Traditional BI and dashboarding systems start with a blank canvas and ask users to assemble charts manually. Rippling supports the dashboarding components experienced users expect, but adds an AI-first path: describe the analysis you want, iterate conversationally, and turn the result into a dashboard your team can keep using. All Rippling dashboards automatically obey the permissions inside Rippling, which means that users can share dashboards that are automatically scoped to the viewer. Each manager sees the dashboard with data for only their own team.

AI-generated, but with verifiable SQL

Rippling AI generates a sophisticated SQL query in response to each data query. It understands the Rippling schema, with org-aware and history-aware functions to make it far more capable. Every result is traceable to the exact query it ran, and which records it touched. If an answer looks wrong, you can inspect the SQL.

Rippling AI can handle queries that normally require a data analyst: complex joins across multiple datasets, conditional aggregations, and time-series analyses with historical context. Based on your prompts, it generates the query, configures the chart, and places it on a dashboard. For teams with SQL expertise, the generated query is inspectable and editable. This is a critical capability: when a dashboard influences a personnel decision, payment authorization, or device action, “the AI said so” is not enough.

Rippling also offers some time-saving tricks. For example, you can upload a screenshot of a chart from anywhere (a board deck, or a report PDF) and Rippling AI will recreate it using your own data. Or, you can ask what you should be paying attention to (e.g., “What belongs on a quarterly board dashboard for a 300-person company?”) and it recommends and then builds the reports for your review.

Dashboard generated by combining revenue data from POS and Employee/business data from Rippling. Actual product experience. Sped up for brevity.

The Rippling architecture transforms the BI experience

Unlike standalone BI tools, a Rippling Dashboard is a navigation layer over your operational data, not just a reporting artifact that’s disconnected from it. That’s because data in Rippling benefits from full worker identity around your data. Permissions are therefore governed by your org chart. You can, for example, share reports that inherit permissions scope for the users viewing them — all the way down to the individual records.

Org-Aware Filters

Filter any dashboard to “my direct and indirect reports” and it works, adjusting automatically as your org changes. Each manager who views the same dashboard sees their own data. Sunburst charts and hierarchy visualizations map to your actual department and manager structure, adding or removing layers as the org grows or contracts. Use it to view resolution times in Jira, to study trends in NPS for your support department, or to see retail sales by team and location.

Org-Aware Permissions

In Looker or Tableau, permissions are managed manually. When someone changes roles, increases their scope, or otherwise needs their permissions updated, it’s done by the dashboard’s owner.

In Rippling, permissions are derived. Build the dashboard once, and every viewer gets a correctly-scoped, personalized version that updates automatically as the org changes. Rolling out dashboards to any number of managers requires no per-user access review.

The impact is that your data team no longer needs to manually administer a fleet of constantly-changing dashboards, and their permissions configurations. Managers can rely on their data access to remain reliable.

Build a dashboard once and share it with multiple people. Each store manager only sees the data for their location.

Drill-throughs to actionable records

Because Rippling BI is referring to data that maintains its context, users can drill down to the raw underlying data. And it doesn’t stop at a table of rows. Every record links directly back to the source: an employee profile, a field device asset, or a sales record.

For example, if a chart shows that pipeline coverage is slipping in the West region, it’s painful to then export the opportunity rows and rebuild the context somewhere else just to understand why it’s slipping. Instead, simply drill into the underlying opportunities, see the account owners, understand the manager and territory context, and inspect the records that explain the movement. This is why BI inside an operational software system like Rippling is different from BI inside a BI system like Tableau: the chart is connected to records that still have their context and meaning, which is available to the user.

See the underlying records of any chart, and continue exploring through customizable object pages. Actual product experience.

It’s hard to overstate the value of data that remains actionable, traceable and inspectable, even after it has been processed by your BI tool.

Analysis and action, in one system

Because so many business processes across HR, IT and Finance live inside Rippling, analysis done inside Rippling Data Cloud is immediately actionable in many cases. In a standalone BI system, results might drive actions, but those actions must be taken manually. Often, that means looking up records, copying and pasting them into another system, and then taking some action, which is cumbersome and error-prone.

For example, a user has run an analysis of devices in the field, and identified some that are compromised or orphaned. She wants to immediately remote-wipe those devices. Rather than exporting that list and moving it to another system, with Rippling she clicks directly into those devices and takes the appropriate actions. She can see data about related entities, like the device’s owner. Her analysis and her actions live in a single system, with a closed loop.

Comes with a classic BI foundation

Rippling BI is designed to stand on its own as a general-purpose dashboarding product, not just a set of prebuilt reports. Teams can build dashboards with the core visualization and analysis primitives they expect from modern BI:

• bar, line, area, and scatter charts

• pivot tables

• hierarchy views like sunburst charts

• conditional formatting

• global and conditional filters

• calculated fields and custom metrics

• saved views

• rich text widgets for context

• caching for fast loading and drilldowns

• exports for sharing visuals

One more reason to care: when you have all of this on top of Data Cloud, you no longer need to pay for separate BI seats. Managers across your business can access this tooling directly. And Rippling automatically joins all of this data to worker identities, a critical pivot point in any analysis.

Easy to try alongside your existing stack

Rippling BI combines full business intelligence capabilities with the operational context behind the data, making analysis easier to trust, easier to act on, and is the fastest path for teams to build dashboards that actually drive decisions.

If you’ve already invested in a mature data stack that serves multiple business functions, Rippling Data Cloud doesn’t require dismantling it. Snowflake Zero Copy means your warehouse data participates in the same analytics layer, joined with Rippling operational data, governed by the same permission model, and queryable by Rippling AI with full org context.

If you’re maintaining ETL pipelines into a BI tool primarily to get dashboards that pivot on worker identity, or relying on spreadsheet exports because proper analytics setup was never prioritized, try Rippling Data Cloud instead. The permissions problem doesn’t exist when the analytics live where the data originates. And the insight-to-action gap closes when the dashboard and the operational system are the same thing.