Merge data

Consolidate and reconcile data from multiple sources for SAF-T reporting.

Organizations frequently need to combine financial data from multiple sources to create complete SAF-T submissions. Sovos SAF-T provides powerful merge functionality to manage this consolidation process while maintaining data integrity.

Multi-system challenges

Organizations that use multiple systems face several SAF-T challenges:

Data structure variations: Different systems store similar information differently, with varying chart of accounts structures, customer codes, and transaction classifications.
Timing differences: Month-end procedures vary between systems, with some processing in real-time while others use batch processing at different intervals.
Master data inconsistencies: Customer information, product codes, and tax codes exist differently across systems, leading to validation errors if not properly managed.

Understanding the merge process

The merge process combines two or more data streams into a single consolidated output. In SAF-T reporting, merging is essential for combining information from different systems and creating a unified view of your financial information.

When data is merged, Sovos SAF-T recalculates all repository data, including tables, KPIs, and rules, to ensure consistency and accuracy across the consolidated dataset.

Merge criteria and collision detection

Effective merging requires clear criteria for identifying records that might represent the same business entity or transaction. When Sovos SAF-T detects records with matching unique identifiers from different sources, these are flagged as "collisions" that require resolution.

Sovos SAF-T uses several fields as unique identifiers for detecting collisions. When records share the same values for these key identifiers but contain different data in other fields, a collision occurs that must be resolved according to your merge strategy.

Document identifiers: Combinations of document type, series, and number
Periods: Accounting periods (months 1-12) within the fiscal year
Entity information: Tax entity or business unit identifiers
Transaction types: Categories of financial transactions

Merge strategies

Sovos SAF-T offers three primary merge strategies, each appropriate for different scenarios:

Incremental merge

The incremental strategy always adds new information to existing data without resolving conflicts and prioritizes completeness over resolving potential duplicates or conflicts. This approach simply inserts new rows into tables and is appropriate when:

Each source system manages distinct data with no overlap
You need to build a comprehensive dataset from complementary sources
Historical data needs to be preserved alongside new information

Recent merge

The recent strategy assumes that newly received information represents the complete dataset needed for the reporting period. This approach truncates old information and writes new data, effectively resolving collisions by always considering new data as authoritative.

This strategy is appropriate when:

A single system is the definitive source of truth
You receive complete replacement datasets rather than incremental updates
Previous data may have contained errors that have been corrected in the new dataset

Recent Incremental merge

The recent incremental strategy offers the most sophisticated approach to data consolidation. This approach achieves full consolidation of both datasets (all from previous files, all from new files), with collisions resolved using the fresh data. The recent incremental strategy is ideal for organizations with multiple source systems that may contain both unique and overlapping data. This method:

Checks for conflicts/collisions between existing and new data
Uses new information as the source to resolve collisions
Retains data existing only in previous files
Adds data existing only in new files

Managing merge collisions

Sovos SAF-T's Merge Collisions functionality provides visibility and control over how data conflicts are identified and resolved.

The Merge Collisions screen displays records where potential conflicts have been detected. Sovos SAF-T identifies collisions by comparing key fields across imported files and flagging records with matching identifiers but different content.

For example, when looking at the Period columns for a particular entity and fiscal year, any period column showing a value greater than 1 indicates a collision has been detected. This means multiple records exist for the same period, requiring resolution according to your merge strategy.

To analyze merge collisions, you must first apply two mandatory filters:

File type (SAF-T or CSV)
Fiscal year

These filters allow you to systematically review and understand collision patterns, which can help identify underlying data management issues in source systems.

When a collision is detected, Sovos SAF-T applies the selected merge strategy to determine which data should be preserved:

With the incremental strategy, both records are maintained, potentially creating duplicates
With the recent strategy, the newer record completely replaces the older one
With the recent incremental strategy, the system keeps unique records from both sources and uses the newer data to resolve direct conflicts

For the recent incremental approach, this means:

Data existing in previous files but not in new files is kept
Data existing in new files but not in previous files is added
Where the same data exists in both sources (collisions), the newer information is used

Practical example of merge operation

To illustrate how merging works, consider two source files containing general ledger movements:

File A contains accounting movements with identifiers JR20001-JR20003, each with associated account IDs, debits, and credits.

File B contains different movements with identifiers VC99001-VC99003, also with their own account IDs, debits, and credits.

When these files are merged:

All unique records from File A are preserved in the output
All unique records from File B are added to the output
If any records had the same identifiers but different values, they would be resolved according to the merge strategy.

The resulting consolidated data includes all movements from both sources, providing a complete view of financial activity for SAF-T reporting.

By understanding and effectively managing the merge process, you can ensure that your SAF-T submissions accurately represent your organization's financial activities even when data comes from multiple systems.

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