Data Scraping Encyclopedia>Data Scraping Noun> Data Integrity

Data Integrity | Web Scraping Tool | ScrapeStorm

2025-07-28 14:10:31

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Abstract：Data integrity refers to maintaining the accuracy, consistency and reliability of data throughout its life cycle. ScrapeStormFree Download

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Introduction

Data integrity refers to maintaining the accuracy, consistency and reliability of data throughout its life cycle. This concept aims to ensure that data will not be changed or lost without authorization during collection, storage, transmission and processing, and always remain in its intended state. Data integrity plays a vital role in many fields, mainly in information systems, databases, cloud services, healthcare, finance and government.

Applicable Scene

Situations in which data integrity is particularly important include the management of medical records, the storage of financial transaction data, the preparation of government statistical materials, and the maintenance of consistency of spatial information such as BIM and GIS. For example, in geographic information data used for urban planning, surveying accuracy and attribute consistency are extremely important, and errors or omissions can significantly impair the reproduction of the real world.

Pros: First of all, reliability is ensured. Guaranteed data accuracy helps to avoid incorrect decisions in decision-making, analysis, and reporting. Furthermore, it makes audits and compliance easier, which is essential especially in the medical, pharmaceutical, and financial industries. In addition, using complete data can be expected to improve the accuracy of automated processing and AI analysis.

Cons: Building mechanisms and systems to maintain integrity is often costly, which can be a burden especially for small and medium-sized enterprises. In addition, overly strict consistency checks can impair the flexibility of data input and processing. If data changes are not easily allowed, there is also a concern that business speed and responsiveness will decrease.