Data & BI Integrations for FP&A | Cube

Integrations · Data & BI

Your data stack, connected. Every driver, one governed model.

Data and BI integrations are governed connections between your data stack, warehouses, databases, and BI platforms, and your FP&A stack, so operational drivers flow into your model automatically instead of through exports. Cube connects to Snowflake, BigQuery, Redshift, Databricks, Tableau, and any SQL source.

…and more

Don’t see your system?

We build custom connections to nearly any system or flat file. Tell us what you run and we’ll scope the connector.

Featured integrations

The data platforms most Cube deployments connect first. Every card opens the full integration guide.

See it on your own tables.

Bring one schema or a read-only role. You’ll see your drivers mapped and reporting beside the GL in Cube.

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What changes when drivers leave the CSV behind?

The workflow, row by row. Both columns are honest.

The workflowManual exportsConnected to Cube
Getting driversAsk the data team for an export, wait, paste.Drivers sync on a schedule, mapped to your model.
Finance + opsFinancial and operational data live in different tools.GL actuals and warehouse drivers share one governed model.
Metric definitionsEvery dashboard computes revenue its own way.One definition, governed in the layer, used everywhere.
Refresh cadenceMonthly, or whenever someone reruns the query.As often as you schedule it, or on demand.
AuditWhich query produced that number?Every figure traces to the source row.
Ready to retire the CSV hand-off?A demo walks your own drivers: connect, map, and watch the model refresh.

Every connection, governed.

Read the security overview →
SOC 2 Type IIAudited controls across the platform, connections included.
Encrypted end to endCredentials and data encrypted in transit and at rest.
Least-privilege pullsRead-only where systems support it. Write-back only where you enable it.
Every sync loggedA full audit trail of what moved, when, and by whom.

Where your drivers land

Governed drivers flow into the tools your team already lives in. Your workflows stay; everything underneath gets smarter.

Claude, ChatGPT, and Copilot work from governed finance data via Cube MCP.

What are data & BI integrations?

Data and BI integrations are governed connections between the systems that hold your operational data, cloud warehouses, databases, and business intelligence platforms such as Tableau, and the planning, reporting, and analysis tools a finance team uses. The integration syncs operational drivers and curated metrics on a schedule, maps tables and data sources to the accounts and dimensions finance plans by, and keeps every downstream number tied to its source row.

In Cube, those connections feed the Agentic Finance Layer, so the same governed drivers power every FP&A workflow: driver-based planning, forecasting, variance analysis, and reporting in your spreadsheets. Accounting, HRIS, and CRM sources join the same model; explore the full FP&A integrations library, the guide to accounting software integrations, or the security overview for the controls behind every connection.

See your data stack in the model.

A demo personalized to your stack: your warehouse, your BI stack, your reports.

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No prep needed. Just bring the names of your source systems.

Questions finance teams ask.

Yes. Snowflake, Google BigQuery, Amazon Redshift, and Databricks connect through Cube's warehouse connectors, and any engine with a JDBC driver connects through direct SQL, with no custom build.
er that gives AI assistants governed access to a company's financial model, with permissions and transaction lineage enforced on every query. The Cube MCP Server is that layer for your Cube model: the assistant asks in plain language, and the answer comes from the same governed model Cube delivers everywhere work happens, with the source transaction one click away.
Yes. SQL Server, PostgreSQL, MySQL, Oracle, Azure SQL, and any other JDBC-capable database connect the same way a warehouse does: a read-only role, a schedule, and a mapping into your model.
Setup is finance-led with one ask of your data team: a read-only role scoped to the tables finance needs. From there your team reviews the proposed mappings and approves them, with guided onboarding from Cube.
On a schedule you control. Most teams sync daily, and more frequently for metrics that move during the day. You can also trigger a sync on demand.
Yes. Operational drivers from the warehouse land in the same governed model as your accounting actuals, so revenue per unit, cost per customer, and driver-based forecasts read from one place instead of a stitched spreadsheet.
Cube connects to BI both ways. As a source, it pulls the curated data sources and metrics your team already maintains in platforms like Tableau, Looker, and Power BI. As a destination, those same dashboards read the governed numbers Cube maintains, so finance and BI finally agree.
Yes. The Cube MCP Server speaks the open Model Context Protocol, so your platform team can point any agent framework at the governed model. Custom agents inherit the same role-based access, audit trail, and transaction lineage the FP&Agents use, so every figure they return is one your finance team can stand behind.
Yes. Cube's patented bi-directional sync fetches live drivers and actuals into your spreadsheets and publishes plan inputs back to the governed model, so the spreadsheet stays a first-class surface rather than a copy.
The operational drivers your plan actually moves on: product usage, pipeline snapshots, billing events, headcount cuts, and unit economics. Cube maps those tables to the accounts and dimensions finance plans by, and leaves the rest of the warehouse alone.
 
The Cube MCP Server connects Claude, ChatGPT, Copilot, and any MCP-compatible assistant to a trusted financial model, so answers arrive decision-ready and trace to the source transaction.
 
Generic database MCP connectors return rows without context, permissions, or lineage.
When schemas change or new tables appear, Cube's Data Manager agents propose the mapping with a confidence score, and finance approves or adjusts it. Every change is logged, so the model stays clean and auditable.
An accounting integration pulls structured financials, the general ledger, from systems like NetSuite or QuickBooks. A warehouse connection pulls operational data, like pipeline or usage, from Snowflake or Databricks. Cube supports both, so financial and operational drivers live in one model.