What is meant by data integrity?

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The integrity of a data refers to that attribute or quality inherent to the data when it is considered truthful, complete, homogeneous, solid and consistent with the intention of the creators of the data that compose it.

This quality, which is linked to the data itself and not to where it is stored, contrary to popular belief; is obtained when it effectively prevents content of a database, of a procedure or system looks, accidentally or intentionally:

– Modified, based on your own content or with the help of inserting it again.

– Totally or partially destroyed.

In Powerdata we use tools focused on validate data attributes, especially in regards to its quality, attending to each one of them as a whole, In other words, as an exact data, complete and homogeneous.

data integrity

The relevance of data integrity

The data integrity It is decisive in any organization, the sector to which they are dedicated and even their size are indifferent when considering this matter and this can be illustrated with simple examples that represent common situations:

– Medication administration in a hospital: any modification in the electronic records of a patient's treatment It could have very serious consequences for your health if, as an example, the dose is multiplied or reduced, changing any of the figures for the daily dose you need of a certain drug.

Incentive administration of the Human Resources Department: modify or delete data within payroll information It can lead to a non-payment or an inaccurate calculation that does not coincide with the conditions negotiated with the worker.

Preparation of an administration report: If he integrity necessary between systems, This lack of integrity will affect your relationships in the first place., which will make the reports unable to benefit from the Business intelligence and it is not, in no case, reliable or valid; situation that could materialize in the existence of breakdowns when crossing the total sales with the warehouse stock.

The bottom line is, therefore, Not only ensure data integrity, but they have the ability to discover if something goes wrong, being able to detect anomalies in time. We take care of that in Powerdata, when we validate the quality attributes to position the level at which each company is in terms of data quality, ensuring that margin of reaction that on so many occasions is decisive.

Data security, from protection to referential integrity

At the same time, when talking about the relevance of data integrityIt cannot be ignored that this attribute of the information is one of the fundamental components of its security. Protection has to be exquisite, especially when we scale in level of criticality and also when we talk about data being exported to non-company environments.

This aspect must be taken care of even more when the data is exported to environments outside the organization. The most common example would be outsourcing, which by definition is a vulnerable environment for information security So what, if you neglect, can affect:

– In the image of the company.

– To business volume.

– Could have legal consequences.

– In summary, it would also affect internal administration.

We cannot fail to mention another facet of the concept of security of the information, what has to do with the reference. The Referential integrity has the necessary technology to protect sensitive information, applying masking processes, as an example, in which, at the same time changing the actual value of the data, it is necessary to maintain that integrity between them.

Ensuring that data masking allows data to be used unrealistically, turning them into an absolutely complete data set and not close to reality, It is essential both in simulations and in production or development environments, where information protection cannot compromise integrity.

Photo credits: “Balance of spheres” by Danilo Rizzuti

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