Data Quality: Data integrity

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The implementation of the new RGPD regulations and the introduction of laws protecting privacy are leading companies to integrate the notion of accuracy of stored data, in addition to guaranteeing its security. A mistake or error in implementing these strategies can result in heavy fines for the company.

How to define data integrity

The accuracy, consistency and completeness of the data are the elements that go to make up the integrity of the data. Integrity must also take account of standards or other rules laid down by legislation, by proposing and implementing precise processes.

At the heart of data integrity lies data quality.

In fact, the primary objective of data integrity is to ensure and guarantee data quality, thus enriching your database.
Your actions arising from the use of your database will be all the more reliable and profitable for having a complete, correctly identified and stable stock of data.

The importance of data integrity

Data integrity benefits your organization in a number of ways:

Reduce the risk of data leakage or loss:
Correct data processing, verification tools, data validation, error analysis, implementation of corrective measures... All these elements indicate that the storage and categorization of your sensitive data is effective and efficient.
Strategic decision-making
Storing correct, up-to-date and reliable data enables you to carry out detailed analyses, enrich your customer vision and make the right decisions. Conversely, incomplete or inaccurate information can have disastrous economic and organizational consequences.
Your corporate image
Collecting customer information known as personal and identifiable information or PII (name, address, bank details...) is the most sensitive type of data collection for your company's image. If an error or incident occurs, whether intentional (hacking attempt) or unintentional (data entry error), this sensitive information can be recovered, disclosed or even misused.
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Data integrity must therefore be considered in its entirety, not just as a legislative constraint, but as a real asset for your company.

Data integrity assessment

Several measurable indicators can be used to assess the level of data integrity within your systems. This level of integrity will provide a complete snapshot of your databases, their level of quality and their usefulness. These indicators include :

Data security, integrity and quality: contradictory concepts?

Security, quality and data integrity are all part of the same package. One cannot exist without the other, and to think that the company can separate itself from one of them would be damaging.

Data integrity will impact the quality of your data by ensuring that there are no duplicates in your system. However, the absence of duplicates does not guarantee the veracity of the data recorded.

Protecting your data against malicious acts, or securing your data, enables you to maintain data integrity.

The success and profitability of strategic decision-making (marketing, sales, IT, product) depend on the integrity and quality of the data collected. Maintaining this integrity is a demanding, day-to-day task for which Data Enso provides support.

We propose to become your partner in your data reliability processes by implementing one of our Data Quality Management solutions.

Our validation, verification and enrichment solutions can be integrated into your collection tools both in real time(preventive mode) and in batch processing(curative mode).