Data breaks when the chart of accounts changes
Finance teams update their chart of accounts or dimensions regularly—yet the underlying pipelines aren’t modular, leading to broken reports and delays in close.
A data platform you can bet money on
Build a modern data platform you can trust with Dagster’s best-in-class orchestration, observability, and reliability. Put your ML models to work with a unified view across all your data assets.
Your data should pay dividends
Revenue, P&L, and accounts receivables are never fixed datasets. It’s constantly changing everyday, and finance is forced to manually pull data from all sources.
Too many manual checks before generating reports
Before reporting to leadership, teams manually compare numbers across systems (ERP, billing, spreadsheets) to catch discrepancies—wasting hours each month-end.
When numbers don’t match, no one knows why
If revenue or cost reports look off, teams have to reverse-engineer the entire pipeline across systems to find the issue. There’s no easy way to trace or debug it.
Pull data, run compliance workflows, push them to your report
Dagster automates pulls across all your financial tools, provides built in data QA to provide real-time financial oversight, and makes it easy for finance to go into dagster, pull the data they need, and plug it into their reports.
Automate financial data pulls from your stack
Developers and data engineers can connect ERPs, invoices, banks feeds as normal
Run automated data QA checks
Ensure your stack is providing real-time financial data, you can schedule this daily, weekly, bi-weekly, monthly.
Know exactly where the data discrepancies are
Zone in on where failed runs happen, why they happen—Seasily push to your data team to fix.
How a finance team automated their month-end close with Dagster
Zippi transformed their data operations by implementing Dagster, enabling better ML integration, improved pipeline monitoring, and enhanced collaboration across teams. The Brazilian fintech startup's journey demonstrates how a unified data platform can eliminate silos while supporting incremental innovation and growth.
Read the full case study
End-to-end orchestration and visibility
Dagster now automatically ingests data from NetSuite, Snowflake, and Excel sheets on a defined schedule.
Reduced data spend and expand
data capabilities
Built-in tests check for missing accounts, duplicate entries, or currency mismatches—before the data is used in reporting.
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The latest news, technologies, and resources from our team.
Blog
The Data Plane Is Yours: Dagster+ Hybrid on Kubernetes and Azure
This article draws on a Dagster+ Hybrid deployment on Kubernetes and Azure at a very large enterprise. It covers the work outside the Helm chart: workload ownership, isolation, networking, identity, sizing, and capacity.
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Blog
Orchestration is More than Scheduling: Declarative Automation in Dagster
Define the outcome, not the orchestration. Declarative Automation lets you express your desired asset state while Dagster continuously handles the work needed to achieve it.
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Case study
Flo Energy's Data Platform for Critical Energy Data
Flo Energy transformed meter, weather, market, and strategy data into a unified, observable platform with Dagster.
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