Fourth to Amazon S3 integration
Connect Fourth to Amazon S3 and automatically sync your finance & accounting data. Weld extracts data from Fourth, loads it into Amazon S3, and lets you transform the data using SQL or dbt, no custom scripts required.
Source
WarehouseSourceFourthConnected- employee36 cols
- payroll22 cols
- employment45 cols
- shift36 cols
- shift_forecast36 cols
- employee_payslip26 cols
- Extract
- Load
- Keep in sync
DestinationAmazon S3Ready- fourth.employeeSynced
- fourth.payrollSyncing
- fourth.employmentSynced
- fourth.shiftSynced
- fourth.shift_forecastSynced
- fourth.employee_payslipSynced
- Fourth tables
- 33
- fields, typed
- 565
- relationships kept
- 17
- agent context included
- MCP
Trusted by data and AI teams
How to set up Fourth to Amazon S3 in Weld.
In the app, with the API or an agent.
New connectionFourthAuthorisedWhy sync Fourth to Amazon S3?
Ready for analysis.
Centralizing your Fourth data in Amazon S3 lets you join it with other data sources for cross-platform analytics and deeper insights.
Build reliable dashboards and reports by querying Fourth data directly in Amazon S3 using SQL or your preferred BI tool.
Financial reporting
Centralize financial data from Fourth in Amazon S3 for automated financial dashboards and month-end close analysis.
Centralized data warehouse
Bring Fourth data into Amazon S3 alongside other sources to create a single source of truth for your organization.
Automated reporting
Replace manual exports and spreadsheet-based reporting with automated pipelines from Fourth to Amazon S3. Connect BI tools like Looker, Metabase, or Power BI.
What data can you sync?
Every Fourth table, keys intact.
Weld syncs the objects the Fourth connector exposes into Amazon S3, and you choose which tables and fields to include. The connector's docs list what is available.
- employee
- payroll
- employment
- shift
- shift_forecast
- employee_payslip
- payroll_forecast
- employee_next_of_kin
- employee_pay_part
- employee_address
- employee_payment_details
- employee_absence
- employee_document
- employee_accrual
- staff_skill
- employee_payroll_period
- employee_passport
- employee_country_specific
- contractor_shift
- fixed_task
- minimum_staffing
- budget
- sales
- sales_forecast
- employee_import_log
- sales_type
- labour_daily_summary
- productivity_analysis
- fixed_cost
- employee_location
- and 3 more
Ask your agent.
It queries Amazon S3 for you.
Connect Claude, Cursor, ChatGPT or your own agent to Weld over MCP. It reads the Fourth context, finds the tables it needs and runs the query in Amazon S3.
How many employee rows do we have per employee? Use our Fourth data in Amazon S3.
Reading the Fourth context first, so the query uses the right tables and keys.
Technical considerations.
What to expect.
- Incremental syncing
- Weld uses incremental syncing where supported by the Fourth API, loading only new and updated records to minimize data transfer and warehouse costs.
- Schema handling
- Weld automatically manages schema changes. If Fourth adds new fields, they're detected and added to the corresponding Amazon S3 tables.
- Data freshness
- Sync frequency depends on your Weld plan. Most connectors support schedules from every 5 minutes up to daily intervals.
- Security
- All data is encrypted in transit (TLS) and at rest. Weld is SOC 2 Type II compliant and supports IP whitelisting for database connections.
Keep reading.
Guides, docs and schema.
Common questions.
About Fourth to Amazon S3.
Start syncing Fourth to Amazon S3.
Set up your Fourth data pipeline in minutes. No credit card required. Free for 14 days.
SourceWarehouse
