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SAP S/4HANA posting date, document date, and posting period rejection diagnosis

A posting rejection is usually a period-control issue, not a document-date mistake. The journal entry date is the document issue date, while the posting date determines the posting period that the system checks. The posting period variant, not the fiscal year variant, opens and closes periods for the header and for each account type.

SAP S/4HANA / posting date / document date / posting period variant / fiscal year variant / period control / authorization / FI document

Understanding Cache-Control Headers for Public and Personalized Responses

This document explains the Cache-Control HTTP headers 'no-store', 'no-cache', and 'private', detailing their distinctions in controlling caching behavior for public and personalized responses, along with browser diagnostics and common pitfalls.

Cache-Control / HTTP / Caching / Web Development / Privacy / Security / Browser / CDN

Evaluating prediction intervals with empirical coverage and width

Prediction intervals aim to contain future individual observations, while confidence intervals target a mean or other parameter, and the two are not interchangeable. Empirical coverage is the held-out fraction inside the interval and width is the distance between quantile limits; a constructed five-value example gives 80 percent coverage and mean width 1.8.

prediction interval / confidence interval / quantile regression / empirical coverage / interval width / scikit-learn / calibration / held-out evaluation

Choosing RAG Chunk Boundaries and Overlap to Preserve Section Context

This article explains how to choose effective chunk boundaries and overlap in retrieval-augmented generation (RAG) systems, comparing fixed-size and document-aware strategies. Using a hypothetical support note example, it demonstrates the risks of splitting across semantic units and shows how metadata and overlap can preserve context. The guidance is based on Microsoft Azure documentation for chunking in vector search and RAG workflows.

RAG / chunking / Azure AI Search / information retrieval / document processing