WHAT IS DATA INTEGRITY AND WHY IS IT IMPORTANT FOR YOU?

By Henning Lund - June 04, 2020

Data is really nothing more than another word for information. Data is one of the most valuable assets of any company. Many claim that it is changing the face of the world.

Data can help companies benefit in several ways. It can help them boost their revenue. They can use it to build themselves up more efficiently or target their audience with personalized ads. They can even find a cure to a disease.

The better quality of data a company has, the more successful it is likely to become. This is where data integrity becomes key. Businesses are asking "What is data integrity exactly and why is having clean and relevant data so important for a business?"

WHAT IS data integrity?

Data integrity refers to the accuracy and consistency of data stored in a database or a data warehouse. Data with “integrity” is said to have a complete structure, i.e. all characteristics defining the data must be correct. Therefore, many are wondering how to achieve data integrity.

Some people talk about the physical integrity of data. This refers to the process of storing and collecting data in the most correct way, maintaining its accuracy and reliability.

The logical integrity of data, on the other hand, checks whether data is correct and accurate in a specific context.

Data integrity constraints refers to the rules applied to maintain the quality of your data. For example, this can be domain integrity or entity integrity.

There are many ways to maintain data integrity and completeness of data. We will explore these options after taking a look into the importance of data integrity for your organization.
data integrity and data reliability are closely linked

 

Why is data integrity important?

Your staff needs to have constant access to data of quality data. Data integrity is important as it guarantees and secures the searchability and traceability of your data to its original source.

Data performance and stability also increase when you ensure effective data accuracy and data protection. Maintaining the integrity of data and ensuring the completeness of data is essential. Compromised data is of no use for most companies.

This includes big data. Organizations collect more and more data and it has become a priority to secure and maintain the integrity of this data. Without integrity and accuracy, your data is worthless.

If you fail to do so, your data could be compromised. In this case, cumbersome and expensive data audit trails could be necessary to trace errors and recover the data.

data integrity gives you data you can rely on to conduct successful business

Data is now more important than ever and most companies have set specific goals for their data. But without integrity, data is not of much use. Moreover, data loss, corrupted or compromised data can considerably damage your business. Ensuring data security has become a number one concern of many organizations.

Data integrity can be compromised in many different ways. Data is mostly digitaland is transferred online in a number of places,. This results in an increasing amount and varied types of data being collected.

For example, data should remain unaltered whenever it is transferred or replicated between updates. As a result, data integrity and data integration can be closely related.

Data is not static, stored once and for all in your systems. Many things can alter your data from the very first day it is created in your system and throughout its lifecycle. It can be transferred to other systems, altered and updated multiple times.

Organizations typically use several management systems (ERP, CRM, SCM, etc.). Things such as human interactions, data transfers, software viruses or compromised hardware can compromise your data’s integrity. This is where maintaining data integrity can become a tricky task.

In my job, I am accustomed to providing data integration solutions to organizations. I am also used to discussing data quality and data integrity in great details with various companies. Most of my customers know that it is crucial to improve data integrity.

Data integrity should be at the top of your mind at every stage of your data lifecycle. From the design and implementation phase of your systems. Data integrity also ensures recoverability and searchability, traceability and connectivity. Protecting the validity and accuracy of data also increases the stability and performance of your systems.

How do you secure data integrity?

What helps to ensure data integrity? Ensuring the integrity of your data within a database at its design stage through the use of standard rules and procedures. Error checking and validation routines can ensure that data hasn't been compromised between transfers and updates. This has to be done at every step in every process.

Preserving data integrity should be the top priority of your organization.

  • Data cleaning and maintenance: make sure to do this on a regular basis, and implement a regular routine to ensure it is consistently done.
  • Data entry training: train your users on how to enter and maintain data, and make them accountable for data quality.
  • Data validation rules: no matter how careful you are, human errors are almost unavoidable. Data validation rules will control and restrict the values that users can enter into their system.

 

NEXT STEP TO ENSURE THE integrity of your data

Is maintaining data integrity at the top of your mind? What are the actions and rules that you have put in place to secure data integrity in your organization?

Have you ever considered protecting and securing the data integrity of your company? Healthy data could save costs and spare you the trouble of dealing with compromised data.


About the author

Henning Lund

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With over 25 years’ experience in strategically propelling businesses forward, Henning is considered a business development entrepreneur with a passion for transforming businesses, sales and marketing operations through out-of-the-box thinking, concepts building and process automation to improve overall performance and scalability.

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