Datakvalitetslivscykel

Datakvalitetslivscykel refers to the ongoing process of managing and improving the quality of data throughout its entire lifespan. This lifecycle encompasses several key stages, starting with data creation or acquisition. During this initial phase, establishing clear data standards and validation rules is crucial to ensure that data is captured accurately and completely from the outset.

Following acquisition, data undergoes processing and transformation. This stage involves cleaning, standardizing, and integrating data from various sources. Techniques such as deduplication, error correction, and format standardization are applied to enhance data usability and consistency. As data is utilized for analysis, reporting, or operational purposes, its quality is monitored. This involves ongoing checks and metrics to identify any degradation or new issues that may arise.

Data storage and archival are also integral parts of the lifecycle. Ensuring data is stored securely and in a format that preserves its integrity over time is essential. Finally, the lifecycle concludes with data retirement or deletion, where data that is no longer needed is disposed of responsibly, adhering to relevant regulations and policies. Throughout each phase, a proactive approach to data quality management is paramount, involving continuous assessment, improvement, and governance to maintain trust and reliability in the data.