SAG / ARCHITECTURE NOTE

Monthly Data Model: How One Month Selection Becomes the Standard Across Every Menu

This data contract uses the month selected in the customer workspace as the shared basis for queries, aggregation, and page navigation. If SEO reads September while GEO reads the latest data, the numbers in one report do not describe the same period. Even if the interface is fast, comparisons become unreliable.

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What Is a Month-Basis Contract?

It is a data contract that uses the month selected in the customer workspace as the shared basis for queries, aggregation, and page navigation. This note treats a month-basis contract in terms of the responsibilities for inputs, transformations, and outputs rather than as a feature name. To trust an analytical result, it must be clear what data was received, what was checked, and how far the conclusions can go.

Why Is This Technology Needed?

If SEO reads September while GEO reads the latest data, the numbers in one report do not describe the same period. Even if the interface is fast, comparisons become unreliable.

Design Principles and Data Flow

Fix the month key, time zone, and start and end boundaries. Check that menu navigation, URL queries, and the cache pass along the same month, and include the period in the server response as well.

Selected month → Period validation and query → Consistent menu data

Each stage must not recharacterize the success of the previous stage as an achievement of the next. Recording data identifiers, periods, and validation status continuously helps locate where omissions and errors occurred and determine what needs to be checked again.

Connection to the SAG Architecture

SAG customer menus query data based on the selected month. If the requested month and the response period differ, the client checks that it does not apply an incorrect result to the screen.

SAG's operational value lies in connecting this relationship to pages and questions, comparison results, and improvement work. Rather than reading numbers alone, customers can review both what needs to be strengthened and the basis for their decisions. Patterns that require additional application should be interpreted within the scope of the relevant paragraph.

Illustrative Example and Evaluation Criteria

For illustration, select 2026-10. Even after moving from SEO to GEO, the October data currently available should continue to be read. If a published report contains data closed out at the end of September, specify the separate analysis period.

The example above is provided to explain the structure and calculation; it is not measured performance from a specific customer. In an actual report, the selected period, target, observation conditions, and source records must be linked so that the same decision can be checked again.

Practical Validation Checklist

Flow stageWhat to check
Selected monthMonth matches across URL, cache, and response
Period validation and queryValidate time-zone boundaries
Consistent menu dataPreserve the basis when switching menus

Check that the same meaning is preserved not only with valid inputs, but also with empty data, duplicate data, and data with different conditions. Linking validation items to the criteria for completing work can reduce the gap between the feature description and actual operations.

Limitations and Considerations for Use

A month key alone does not automatically resolve UTC/KST boundaries. Regression-test month-end and year-end transitions, as well as reporting standards that vary by region.

Research and Official Documentation

  • PostgreSQL JSON Types — Official documentation describing the characteristics and constraints of JSON storage types.

External sources provide background on the design topic above; they do not certify every SAG implementation or customer outcome. The application interpretation and illustrative example in this note are organized according to SAG's operational structure. Data checked: 2026-10-06.

Further Reading and Feature Information

How to Continue Reading About This Technology

Distinguish monthly samples, the denominator for citation rate, competitive benchmarks, and Goal attainment rate.

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