Month: May 2024
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Handling Hierarchical Tidy Data in Financial Reporting
Views: 8 Handling Hierarchical Tidy Data in Financial Reporting Nobuyuki SAMBUICHI In this blog post, we will explore how to handle hierarchical tidy data in financial reporting. We will discuss how to merge necessary data into target rows to summarize amounts based on debit/credit codes, account numbers, and months, ensuring efficient data management and avoiding redundancy. 1. Characteristics of a hierarchical tidy data Hierarchical tidy data reports different levels of observation in different rows, resulting in no redundant report files. However, we need to merge necessary data into a target row to summarize amounts based on debit/credit codes, account numbers, and months. The entered date is reported in a header […]
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ISO/WD 21926 Semantic Data Model for Audit Data Services – Draft for Commenting Period Now Open
Views: 0 ISO/WD 21926 Semantic Data Model for Audit Data Services – Draft for Commenting Period Now Open Nobuyuki SAMBUICHI co-project leader at ISO/AWI 21926 Semantic data model for audit data services We are excited to announce that the draft of the “Semantic Data Model for Audit Data Services” is now open for public commenting. This draft outlines the framework, methodologies, and key elements for establishing a standardized approach to audit data services. Below are the key details and milestones related to this important project. 1. Project Overview 1.1. Title and Scope Title: Semantic Data Model for Audit Data Services Scope: This document establishes a semantic data model for audit […]
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Hierarchical Tidy Data
Views: 9 Hierarchical Tidy Data 1. Wickham’s Definition Hadley Wickham defines tidy data as follows: 1. Each variable forms a column: Each variable in a dataset is placed in its own column. 2. Each observation forms a row: Each observation is placed in its own row. 3. Each type of observational unit forms a table: Each cell contains a single value. This definition of tidy data facilitates data analysis and visualization and allows consistent data handling. It is important to note that tidy data imposes restrictions on the types of observations by specifying “each type of observational unit”. If we remove this restriction and just specify “observational units”,this means that […]
