Zeitpunkt Nutzer Delta Tröts TNR Titel Version maxTL Mi 10.07.2024 00:00:00 51.211 +49 2.182.055 42,6 Vivaldi Social 4.2.10 1.337 Di 09.07.2024 00:01:21 51.162 +41 2.178.939 42,6 Vivaldi Social 4.2.10 1.337 Mo 08.07.2024 00:01:05 51.121 +48 2.178.512 42,6 Vivaldi Social 4.2.10 1.337 So 07.07.2024 00:00:03 51.073 +43 2.174.783 42,6 Vivaldi Social 4.2.10 1.337 Sa 06.07.2024 00:00:28 51.030 +43 2.171.323 42,5 Vivaldi Social 4.2.10 1.337 Fr 05.07.2024 00:00:08 50.987 +26 2.167.586 42,5 Vivaldi Social 4.2.10 1.337 Do 04.07.2024 00:00:11 50.961 +42 2.163.949 42,5 Vivaldi Social 4.2.9 1.337 Mi 03.07.2024 00:00:04 50.919 +42 2.160.792 42,4 Vivaldi Social 4.2.9 1.337 Di 02.07.2024 00:01:14 50.877 +42 2.156.674 42,4 Vivaldi Social 4.2.9 1.337 Mo 01.07.2024 00:01:17 50.835 0 2.153.375 42,4 Vivaldi Social 4.2.9 1.337
ttpro (@ttpro) · 07/2024 · Tröts: 5 · Folger: 0
Mi 10.07.2024 20:26
Accuracy: Data accuracy ensures that the data in the warehouse correctly reflects the real-world object or event it represents. Accuracy is crucial for making reliable decisions and producing trustworthy reports.
Completeness: Completeness refers to the degree to which all required data is present in the data warehouse. Missing data can lead to incomplete analysis and potentially biased results.
Consistency: Consistency ensures that data is uniform and does not conflict with other data stored in the warehouse or with external data sources. Inconsistencies can arise from duplicate records, formatting differences, or conflicting values.
Timeliness: Timeliness indicates that data is up-to-date and reflects the current state of the business or operation. Outdated data can lead to incorrect conclusions and ineffective decision-making.
Validity: Validity ensures that the data conforms to the defined business rules and constraints. Valid data meets the standards and expectations for its intended use within the data warehouse.
Integrity: Data integrity guarantees the accuracy and consistency of data across its entire lifecycle within the data warehouse. It involves maintaining the quality and reliability of data through processes such as validation, error-checking, and adherence to standards.
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