How to ensure data integrity: Best practices for organizations

Data integrity refers to the accuracy, reliability, and applicability of data for internal and marketing use. On a broader scale, the term also encompasses information security and safety, as well as data governance in accordance with local and national compliance standards. Knowing how to ensure data integrity is key. Learn the best practices for maintaining accurate and reliable data.

Why is data integrity essential?

Data quality is immensely important. If data is inaccurate or outdated, you may make decisions out of lockstep with current customer trends and behavioral patterns. It can lead to expensive campaigns that fail to convert and/or customer churns. This is supported by research. A 2018 report from Royal Mail revealed that inaccurate data has led to companies losing an average of 6% of their annual revenue. Another report from the Harvard Business Review found that poor data quality has resulted in $3 trillion in lost revenue for American businesses in 2016. 

Best practices for data integrity

Work with your internal or third-party information technology team to determine the best practices for maintaining data integrity and how to enforce these steps. Here are some practices in use by small businesses and fortune 500 companies across all industries.

Data encryption

Data encryption is a basic yet invaluable cybersecurity tool. When data is encrypted, parties with access to the information will be unable to view it without the decryption key. For maximum data protection, consider asymmetric encryption, which requires separate keys for encrypting and decrypting data.

Stay up to date with data compliance laws   

Compliance regulations are in place to protect the customers’ personally identifiable information (PII). Guidelines like the General Data Protection Regulation (GDPR) cover recommendations on:

• Data validation procedures
• Access restrictions and protocols for data entry controls
• Data recovery and backup planning

The EU’s GDPR is a good blueprint to follow for European-based and non-European companies alike. There may also be data governance regulations specific to your industry. Examples include HIPAA for the medical industry and FISMA for IT sectors serving federal institutions.

Audit the audit trails

Your audit trail consists of your company’s history of financial transactions, including any and all updates to the trail itself. Your IT team should have a system in place, preferably automated, for maintaining database queries, event logs, and electronic records.

Perform penetration testing and audits

How strong is your data security? You may think it’s secure because it has the latest encryption and malware prevention measures. However, cyber-criminals are more adaptable than you may think. After every system update, have an ethical hacker try to penetrate your system. If an ethical hacker can access your system, then so can a hacker with malicious intentions.

Develop process maps for critical data

Process maps provide a visual reference of how, where, and when data is stored. It makes data easier to decipher and organize through a uniform standard for naming conventions, color coding, and symbol attributions. 

You don’t have to have a process map in place for all incoming data, but you should map out first-party data you use for your operational analytics and marketing campaigns. Visual mapping gives you a clear overview of customer data, how to use the information, risk management protocols, and more.

Promote a culture of integrity

All staff given access to the data must pledge to abide by company-established standards for data management, integrity, and security. A culture of integrity entails the following:

• Reporting mishandling of data
• Pledging not to share the data with unauthorized individuals
• Pledging not to handle the data in a way that may put PII at risk (i.e. accessing data on a personal and unsecured device)

Policies should outline the consequences of mishandling data. Depending on the severity of the violation, this may range from revoking access privileges to termination of employment.

Regularly clean the data

Your company accumulates more data over time. The increase in data quantity can unfortunately lead to a drop in data quality. As the data compiles, so do issues like duplicates and older data becoming outdated. This can adversely impact data accuracy, not to mention it consumes storage space and can potentially cause slow-downs. Have a system in place for automatically removing duplicate data and filtering out data that has been in the system for X length of time. Cleaning data also includes reviewing data formats and reorganizing data that may have been misfiled or miscategorized.

How to ensure data integrity with Lytics’ help

We can’t stress the importance of data integration. Data silos are a primary cause of data mismanagement. Data may be left out, duplicated, or not timely updated. This is prone to happen especially if integration is performed manually. Eliminate the human error factor with an automated solution.

P.S. Did you know? With Cloud Connect, administrators have a secure and singular location for integrating data from disparate sources, and it’s all handled automatically. Manage your access controls through an intuitive database to determine user privileges, metrics analysis, and more.