data hygiene for business it teams

In 2025, the total data volume on all connected devices is estimated to be 79.4 zettabytes. Most of this data will be generated by businesses that want useful information on their customers, internal processes, and other things. Data hygiene is a critical process, often undervalued and underestimated in contrast to analytics & cloud infrastructure goals.

But raw data is dirty, unstructured data – and failing to implement best data hygiene practices can lead to staggering revenue loss. Businesses report losing $12.9 million annually because of bad data! But all is not lost. 

Having supported dozens of Fortune 500 companies with data hygiene goals, we know what it takes to achieve data accuracy. In this quick post, we share some of the top data hygiene practices for business and IT teams from experts, including a downloadable checklist for maintaining best practices. 

Let’s roll!

What is data hygiene?

Data hygiene is a list of practices and processes to treat dirty and duplicated data. This is possible with activities such as data validation, cleansing, and standardization that check the quality and integrity of data within a database or system.

Simply put, data hygiene makes it possible for teams to work with structured, clean, accurate data, enabling better insights, informed decision-making, and improved operational efficiency. 

How to enforce data hygiene? Here are a few tips from industry experts.

All Data Hygiene Starts with Data Quality Training

Data hygiene starts with training personnel about data quality.

Most companies presume that having employees collect data in their haphazard manner could work out somehow. The truth is, that your employees need to know how to collect data the right way. For this, comprehensive training on data quality is needed.

Kevin Ameche, President of RealSTEEL Software, underscores the need for data quality training and shared responsibility at the organizational level:

I believe the most crucial aspect for a small business or IT team to improve data hygiene is establishing a culture of data awareness and responsibility across the organization. This starts with education and training.

He suggests simple data quality habits for employee training such as:

❇️Regularly updating and verifying data entries

❇️Understanding the implications of data privacy laws is fundamental to maintaining data hygiene

This foundational knowledge empowers each employee to act as a steward of the data they handle, as part of a proactive environment where data quality is everyone’s responsibility.

Prioritize Data Minimization

Vaibhav Kakkar, CEO of Digital Web Solutions says:

Prioritizing data minimization can significantly enhance data hygiene for small businesses and IT teams. This approach entails only collecting data that is directly relevant and necessary for the intended purpose, thus reducing the risk and complexity associated with data management.

Consider this – businesses rely on multiple sources to generate data. For example, the sales department collects different data than the marketing department. The same goes for IT and business units. Not everyone needs all available information, which results in slow-decision making, increased risk of data leaks, as well as unsustainable data storage and maintenance costs.

When you collect data from multiple sources or systems, you should consider integrating and transforming them into one data store. This can be done by using the ETL (Extract, Transform and Load) integration method. Once you have all the information under one system, consider breaking the data chunks down for different departments based on their needs and requirements i.e. data minimization.

Here are a few tips from Mr. Kakkar on how to protect your data:

❇️Implement strong encryption for data at rest and in transit

❇️Adopt a robust access control system (permission-based, role-based, etc.) to safeguard sensitive information from unauthorized access or breaches

Implement Rigorous Access Controls

According to Alari Aho, CEO of Toggl, a provider of productivity enhancement tools:

The foundation of robust data hygiene lies in stringent access controls. This means ensuring that only authorized personnel have access to sensitive data, tailored to their role and necessity. 

This ‘do-more-with-less-data’ approach has other tangential benefits for organizations. Mr. Aho mentions that this approach:

❇️Minimizes the risk of accidental or malicious data breaches

❇️Makes sure that data flows securely and efficiently to those who need it, when they need it, in the manner most secure and beneficial for the organization’s health and growth.

Hire a Data Quality Strategist

There are many reasons why you may need a data quality strategist:

❇️Your company generates a lot of data from multiple sources every day

❇️Data is the cornerstone of your company’s decision-making and strategic goals

❇️You are unfamiliar with how mismanaged data can invite unwanted attention and penalties from regulatory bodies

A data quality manager can work as a CRM manager or marketing professional, depending on your company’s needs. But they have one primary function – to develop procedures for data evaluation, data management and data maintenance.

Empowering Business Users

Enforcing data hygiene is no longer the remit of IT or data teams only. Rather, the whole organization can do with adopting data quality procedures, especially business users.

What about the skill ceiling when it comes to technically complex processes of data cleaning, matching, and management? Today’s no-code data quality tools make use of an intuitive user interface that can help you accomplish data tasks with relative ease.

“Regardless of their role, every team member should understand the importance of data integrity, how poor data hygiene can affect operations, and the basic principles of handling data securely and accurately,” says Kevin Ameche, RealSTEEL

It is possible for business users, data analysts, and IT professionals to collaboratively work towards strategically aligned goals while ensuring a high degree of trust and confidence in the data they work with.

Identify and address the most common data hygiene issues

Burak Özdemir, Founder of Character Calculator, shares his insights:

The centerpiece of improving data hygiene for any small business or IT team is establishing a consistent and rigorous data quality management process. This involves regular auditing, cleaning, and updating data to ensure accuracy, relevance, and security. Organizations can make well-informed decisions, enhance operational efficiency, and mitigate the risk of data breaches and compliance issues by prioritizing data quality management.

Consider an ecommerce company that has incorrect customer address entries in its database. An incomplete or poor address data results in a rising spate of failed deliveries, affecting the organization’s profitability. This issue keeps occurring due to a lack of understanding of data quality problems.

Teams in your organization should learn about common data quality problems such as duplicates, inconsistencies, and inaccuracies. Most of these problems are commonplace and can be resolved at the source.

As Mr. Özdemir says, “Clean data is the fuel that drives successful businesses.”

Establish a Data Quality Management (DQM) Framework

Businesses and IT teams need to invest in developing systematic processes that monitor data quality consistently at every level. There is also a need to implement a variety of data quality processes – data cleaning, data audits, and data validation.

Kevin Ameche of RealSteel Software states:

Implementing regular audits and clean-up routines is vital. By scheduling periodic reviews of the data stored in our systems, we can identify outdated, redundant, or incorrect information that needs to be corrected or removed. Utilizing automated tools can help streamline this process, but it’s also important to have manual checks to ensure accuracy. 

He suggests adopting a periodic review process where teams critically assess the relevance and accuracy of the data in their purview, ensuring their databases are clean and optimized for operational needs.

With a DQM framework in place, businesses can enhance their decision-making capabilities, as decisions are based on current and accurate information. For example, a company that exercises CRM data hygiene is well-positioned to deliver better customer service than the one that doesn’t.

Investing in Data Hygiene Solutions

We talked about how employees from different departments collect data and can potentially run into data quality issues. To avoid this, businesses and IT teams alike can opt to fix these issues manually or with automated data quality tools.

We take a look at the pros and cons of both:

pros and cons manual data cleaning
A comparative analysis of manual data cleaning
pros and cons automated tool data cleaning
A comparative analysis of automated data cleaning tools

To Conclude – Begin your data hygiene efforts with WinPure’s time-saving features

40% of organizations lack formal data policies. The time taken to maintain data hygiene and clean up data entries outweighs the time spent searching through multiple tabs of spreadsheets. This process demands data quality training for stakeholders and the use of automated data quality tools that can be used by IT teams as well as small businesses with a lower barrier to entry.

Want to try out a data quality tool that aids in your business success? WinPure offers a 30-day demo. Try it and kickstart the process of data hygiene for business and IT teams in your organization.

Written by Samir Yawar

Samir writes about data quality challenges faced by businesses and how it impacts their day-to-day operations. His end goal - help businesses make sense of their data with WinPure's no-code platform.

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