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Master data represents "data about the business entities that provide context for business transactions". [1] The most commonly found categories of master data are parties (individuals and organisations, and their roles, such as customers, suppliers, employees), products, financial structures (such as ledgers and cost centres) and locational concepts.
Besides differences in the schema, there are several other differences between the earlier Office XML schema formats and Office Open XML. Whereas the data in Office Open XML documents is stored in multiple parts and compressed in a ZIP file conforming to the Open Packaging Conventions, Microsoft Office XML formats are stored as plain single monolithic XML files (making them quite large ...
The SIE format is an open standard for transferring accounting data between different software produced by different software suppliers.. SIE could be used to transfer data between software on the same computer, but also used for sending data between companies, for example between the company, the accountant and the audit.
Both free and paid versions are available. It can handle Microsoft Excel .xls and .xlsx files, and also produce other file formats such as .et, .txt, .csv, .pdf, and .dbf. It supports multiple tabs, VBA macro and PDF converting. [10] Lotus SmartSuite Lotus 123 – for MS Windows. In its MS-DOS (character cell) version, widely considered to be ...
Business analytics (BA) refers to the skills, technologies, and practices for iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods .
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
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The study considers that these errors are serious, since XBRL data are computer-readable and users will not visually recognize the errors, especially when using XBRL analysis software. A different conclusion was reached by Du et al., 2013 [24] who argued that companies are going through a learning curve and are steadily improving.
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