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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.
For example, consider the accounts payable department when processing an invoice. With an accounting information system, an accounts payable clerk enters the invoice, provided by a vendor, into the system where it is then stored in the database. When goods from the vendor are received, a receipt is created and also entered into the AIS.
The Portable Format for Analytics (PFA) is a JSON-based predictive model interchange format conceived and developed by Jim Pivarski. [ citation needed ] PFA provides a way for analytic applications to describe and exchange predictive models produced by analytics and machine learning algorithms.
Data analysis focuses on the process of examining past data through business understanding, data understanding, data preparation, modeling and evaluation, and deployment. [8] It is a subset of data analytics, which takes multiple data analysis processes to focus on why an event happened and what may happen in the future based on the previous data.
Financial analysts can also use percentage analysis which involves reducing a series of figures as a percentage of some base amount. [1] For example, a group of items can be expressed as a percentage of net income. When proportionate changes in the same figure over a given time period expressed as a percentage is known as horizontal analysis. [2]
Note: If you really need to get data from a QIF file into an account that does not support QIF imports (e.g. Quicken 2005 and later), you can import from the QIF file into a (temporary) Cash account. Make sure the first line in the QIF file says "!Type:Cash" for importing it into a Quicken Cash account. (QIF files can be edited in any text editor.)
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The difficulty in ensuring data quality is integrating and reconciling data across different systems, and then deciding what subsets of data to make available. [3] Previously, analytics was considered a type of after-the-fact method of forecasting consumer behavior by examining the number of units sold in the last quarter or the last year. This ...