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Systems, Applications, Products in Data Processing, or SAP, was originally introduced in the 1980s as SAP R/2, which was a system that provided users with a soft real-time business application that could be used in multiple currencies and languages.
Industrial process data validation and reconciliation, or more briefly, process data reconciliation (PDR), is a technology that uses process information and mathematical methods in order to automatically ensure data validation and reconciliation by correcting measurements in industrial processes.
Advisory actions typically allow data to be entered unchanged but sends a message to the source actor indicating those validation issues that were encountered. This is most suitable for non-interactive system, for systems where the change is not business critical, for cleansing steps of existing data and for verification steps of an entry process.
Process performance qualification protocol is a component of process validation: process qualification. This step is vital in maintaining ongoing production quality by recording and having available for review essential conditions, controls, testing, and expected manufacturing outcome of a production process.
Extract, transform, load (ETL) is a three-phase computing process where data is extracted from an input source, transformed (including cleaning), and loaded into an output data container. The data can be collected from one or more sources and it can also be output to one or more destinations.
Verification is intended to check that a product, service, or system meets a set of design specifications. [6] [7] In the development phase, verification procedures involve performing special tests to model or simulate a portion, or the entirety, of a product, service, or system, then performing a review or analysis of the modeling results.
It also covers the steps involved in preparing and reporting the overall accounts which are typically stored in a general or nominal ledger and managed by a controller. The detailed steps involved are: [2] data extraction; data collection; data validation; data transformation (generation of voucher) voucher posting (to general ledger)
Data processing may involve various processes, including: Validation – Ensuring that supplied data is correct and relevant. Sorting – "arranging items in some sequence and/or in different sets." Summarization (statistical) or – reducing detailed data to its main points. Aggregation – combining multiple pieces of data.