Maximize the value of your data with best practices in data hygiene
Maintaining accurate company data and customer information is a significant challenge, particularly for larger organizations. To safeguard data and streamline processes, managers must implement effective data hygiene practices. In this article we’ll guide you in how to develop a robust data management strategy for your company.
From the article you will learn:
- What is data hygiene?
- What are data collection strategies?
- What is data cleaning?
- How to set data standards?
- Who should manage the data?
- How automation can help with data hygiene
What is data hygiene?
Data hygiene is the practice of maintaining the accuracy and reliability of information, often referred to as the data cleaning process. It involves standardizing data, removing errors, eliminating duplicates, and discarding outdated information. This process should be ongoing and ingrained in the corporate culture.
Read our article on data hygiene: https://ccaeurope.pl/en/clean-data-clear-path-mastering-data-hygiene-in-your-organization/
Why is data hygiene important?
- Good data hygiene streamlines business processes and enhances convenience. When employees have easy access to accurate data, such as customer contact details and purchase history, workflows become more transparent for both management and staff. This also reduces the risk of errors.
- Clear data storage rules simplify and speed up data entry. This benefits sales and marketing teams, who regularly maintain customer records, add new information, and update the customer base. Additionally, by implementing these data hygiene practices, you can eliminate manual data entry and automate the process.
- Clean data enhances decision-making. When records are transparent and reliable, data-driven insights can be accurately gathered. These insights are crucial for developing effective business and marketing strategies, as well as optimizing production and supply chain management.
- Transparent and regulated data collection ensures safety. In today’s environment, protecting company and customer data is a top priority for any organization. Adhering to data privacy regulations not only eliminates the risk of data breaches but also reflects a company’s commitment to ethical standards.
Best practices for data hygiene
To effectively integrate data hygiene into your workflow, you’ll need a strategy rooted in established quality principles. We’ve compiled a set of data hygiene practices that are beneficial for companies:
Data collection strategy
Defining the purpose and principles of data collection is crucial, particularly when dealing with consumer data. Establish clear data retention and deletion policies, including retention schedules that specify how long data will be stored before it is deleted. This approach ensures that your data management practices are both efficient and compliant.
Maintaining data hygiene is easier when you know:
(1) what data is stored
(2) why it is stored
(3) where and when to delete it.
Regular data audits
Conducting regular audits of all company databases is essential for maintaining data hygiene quality. Focus on these steps:
Data validation:
Review all information to determine if updates are needed. Correct errors and remove duplicate records. This will enhance the company’s marketing and sales efforts, as well as improve production.
System evaluation:
Assess the tools your company uses, such as the CRM, to determine if they meet your business needs. An audit provides an ideal opportunity to reevaluate your current system and make optimizations.
Implement new tools:
If maintaining proper data hygiene is challenging, consider adopting more advanced solutions to streamline the process. These may include services that automate data capture or analysis and sophisticated data protection software.
Access management:
For security reasons, ensure that only authorized employees have access to the database. During audits, review who has access to sensitive data and assess whether permissions need to be adjusted.
Employee training:
Everyone handling data should be well-versed in the company’s core values regarding data hygiene. Regular training is essential to emphasize the importance of meticulous data maintenance. Providing detailed process descriptions will also help new employees quickly grasp these practices. Encourage your team members to actively maintain clean and accurate data.
Data Cleaning
Over time, some data can become obsolete, such as information from a retired system. This data should be deleted in accordance with data protection standards or migrated to a new system if necessary.
Read our case study: https://ccaeurope.pl/en/custom-database-migration/
The deduplication process eliminates duplicate data within a storage volume or across the entire storage system (inter-volume deduplication). It employs pattern recognition to identify redundant data, which is then replaced with references to a single backup. This method is a proven approach for efficiently organizing data sets.
Data standards
Data standards are crucial for ensuring accuracy and consistency. To achieve this, establish clear rules for data collection, specifying what information is needed and creating a straightforward process for employees to follow. Ensure that the same standards are applied uniformly whenever data of the same type is collected, regardless of the context.
Consider the data required for analysis at this stage. For instance, while knowing a customer’s business sector may not be necessary for initial contact, it can be valuable for targeted marketing campaigns. Define key categories and standardize the data collection methods for each to ensure consistency and usability.
Data management
Data hygiene is a shared responsibility among all employees who handle company and customer information. However, one person or a dedicated team should oversee these processes. This includes implementing data quality best practices, conducting employee training, performing audits, and more.
Data management encompasses a set of processes, roles, policies, standards, and metrics designed to use information effectively to achieve organizational goals. It involves defining:
– who can perform specific actions
– on which data
– under what circumstances
– using which methods.
Good management is essential for ensuring data quality within an organization.
Process automation
Data hygiene also involves process automation, which focuses on automatically updating data as frequently as possible to ensure it remains current and accurate. Data cleansing systems utilize algorithms to process large volumes of data, allowing them to detect anomalies, identify errors caused by human oversight, and find duplicate records.
If you’re ready to start cleaning up your company’s database, download our guide: