Finance
Connect operational systems to financial models without another reconciliation ritual.
Finance cannot run the company from ERP extracts that arrive late and operational data that does not share a chart of accounts. Financial analytics on Databricks is about governed models, not prettier charts.
Close, forecast, and operating reviews should not require a parallel data warehouse in Excel.
Operational systems move faster than finance models. When the join is informal, every close re-creates mappings, and executives get two versions of margin.
Chart of accounts lives in people's heads
Mappings from operational products to financial accounts are not a data product.
Actuals and drivers disagree
Volume, price, and cost drivers cannot be tied back to GL actuals at a stable grain.
Access is either too open or too closed
Sensitive financial data is copied into unmanaged extracts or locked away from people who need governed views.
Outcomes
Governed financial models
Actuals, drivers, and allocations documented, permissioned, and lineage-visible.
Faster, more defensible reporting
Close support and management reporting reuse the same gold tables.
Controlled access
Unity Catalog policies replace spreadsheet distribution lists.
How the architecture works
01
Operational-to-finance mapping
ERP, billing, and operational facts aligned to account, cost center, and time.
02
Gold financial products
P&L, margin, and driver models with explicit grain and owners.
03
Consumption under policy
SQL and dashboards for finance; restricted views for the rest of the business.
What we implement
- ERP and operational integration
- Financial grain and allocation design
- Management reporting datasets
- Unity Catalog for sensitive finance data
- Executive financial dashboards
- Auditability and lineage
Where this shows up
Management reporting modernization
Replace a close-time spreadsheet stack with governed gold models.
Operational finance
Give operators volume and cost views that still roll to the same P&L finance signs.
What should be measured
The business case is built on a baseline, not a promise. These are the numbers this solution is accountable to.
- Close and reporting cycle time
- Forecast error by driver
- Number of competing margin definitions
- Analyst hours spent assembling data vs. analyzing it
The first sensible pilot
One governed P&L view with drivers
Model actuals and operational drivers for one business unit at a stable grain, permissioned through Unity Catalog, and use it in one real operating review.
Questions
Is this an ERP replacement?
No. ERP remains the system of record for accounting. Databricks is where operational and financial data are modeled together for analytics under governance.
Can this support audit requirements?
Unity Catalog lineage, privileges, and audit logs are part of the design. Formal audit sign-off remains the organization's responsibility.
Related
Databricks SQL & AI/BI
Building Trusted Executive Analytics on Databricks
Executives do not need more dashboards. They need a small number of numbers that survive contact with finance, operations, and the next question.
9 min
Unity Catalog & Governance
How to Structure Unity Catalog for Enterprise Governance
Catalogs, schemas, groups, and ownership are the governance architecture. Privileges accumulated on individual users are how that architecture decays.
11 min
Start with the business case
Find the first data or AI opportunity worth proving.
We evaluate the business problem, systems, data, architecture, and economics behind it—then identify the smallest production engagement capable of proving whether the opportunity is real.
Business case first · Architecture-led · Production-focused