andmetäpsus

Andmetäpsus refers to the degree to which data accurately reflects the real-world phenomenon it represents. It is a fundamental quality of data that impacts its usefulness and reliability. High data accuracy means that the data is free from errors, omissions, and inconsistencies, and it correctly captures the intended information. Conversely, low data accuracy can lead to flawed analysis, incorrect conclusions, and poor decision-making.

Factors contributing to data inaccuracy can include human error during data entry or collection, faulty measurement instruments, outdated information, or issues with data processing. The consequences of inaccurate data can be far-reaching, affecting businesses, scientific research, and even public policy. For instance, in business, inaccurate sales figures might lead to overstocking or understocking, impacting profitability. In scientific research, erroneous experimental data could invalidate entire studies.

Ensuring data accuracy involves implementing robust data governance practices. This includes establishing clear data definitions, employing validation rules, conducting regular data audits, and providing training to personnel involved in data handling. Data cleansing techniques, such as identifying and correcting or removing erroneous records, are also crucial. In essence, data accuracy is a continuous effort to maintain the integrity and trustworthiness of information.