Data pivot

Purpose

• Standardizes and normalizes raw transaction data across multiple sources before aggregation
• Groups transactions by your reporting dimensions: currency, entity, product, customer segment, and more
• Calculates summary metrics including total transactions, volumes, fees, net cash movements, and balances
• Produces structured pivot tables and pre-calculated reports ready for the next step in your workflow

Inputs

• Raw transaction exports from operational or financial systems (e.g., payments, sales, settlements)
• Aggregation rules that define how transactions should be grouped and summarized
• Reporting dimension definitions specifying how transactions should be categorized for pivot tables (dates, accounts, regions, products, currencies)
• Outputs from other nodes (e.g. reconciliation results that need to be pivoted by error, or by currency)

Outputs

• Structured pivot tables for each reporting dimension
• Pre-calculated analytical reports including totals, averages, medians, and variance against your aggregation rules
• Standardized transaction records, ready to pass to the next node in your workflow

Typical use cases

Raw transaction data needs to be aggregated and structured before it can be used in reporting or accounting workflows.

• Grouping daily settlement transactions by entity and currency to produce a structured summary for your performance reporting workflow
• Aggregating transaction-level data by account type and product before journal entries are posted, so your accounting workflow receives pre-calculated totals instead of raw data