In today’s world, data is an essential fuel that runs any modern company. It assists organizations in making informed choices, understanding and gaining trust of the customers, and tracking general success. Simply said, it is the foundation of all corporate processes. 

The better the data, the better corporate insight, security, efficiency, and overall process organization. That’s why data itself, as well as its quality, plays a crucial role in business.   

According to Gartner, every year, companies all around the globe lose on average $12.9 million as a result of poor data quality. In the long run, bad quality data can not only affect income, but also lead to poor decision-making. This might threaten reputation and the future of your company.

Keep on reading to know more on why you should care about data quality and the main tips to improve it!

What Is Data Quality and How to Manage It?

Data quality describes a state of data: its accuracy, consistency, and overall ability to fulfill specific functions and criteria in a given context. Poor quality data causes a slew of various issues that might seriously harm the company. That’s why data quality improvement strategies can play the major role in the safety net and success of any company.   

Data quality management is a collection of strategies aimed at ensuring the quality of data itself. It combines everything from data collection and deployment of modern data procedures to successful data delivery. The purpose of data quality management is to use a well-balanced combination of solutions to avoid future data quality problems and to clean (or eventually eliminate) data that does not match established quality standards.  

Of course, the standard of good data varies depending on its nature and final requirements of how and for what the data will be used. The main criteria to check on to find out the quality of your data are the following: completeness, consistency, accuracy, validity, and precision. These metrics are primarily to be evaluated before any further step of working with data.   

But what affects data quality? Well, everything from initial missing or incorrect data, human errors, out-of-date information or even programming flaws in software. The list can be long. Therefore, data quality management becomes a missing puzzle piece that will help you to achieve the desired outcome. 

Top 5 Tips to Get Better at Handling The Quality of Your Data

Now, after discussing the importance of data quality and wanting to take action, where do you start? 

• Do your research 

First, you should clearly identify the scope of your project and business needs. It’s worth beginning with answering questions such as: What kind of data do you need to collect? Where are you going to store it? What is the format of your data? Or who will have access to it? 

• Set the standard

You need to be clear about what data quality standards are the best for your organization. Of course, data may not always meet 100% perfect accuracy, but how close to perfect is enough for you? Remember, that data quality standards differ according to data types and future uses. 

• Assess the risks 

It’s important to analyze the impact of poor-quality data on the final outcome. Risk assessment can help in determining which data quality flaws must be addressed right away and which can be solved afterward.

• Protect your data

Data security is critical for consumer trust and corporate insurance. To maintain it, a company’s analytics system must focus on flaws management, encryption development, and authentication.  

• Transparency is the key 

To genuinely achieve data-driven success, businesses must foster cross-functional cooperation and shift towards corporate strategies. The obtained data must be available to all the potential users. It is also a good idea to conduct regular open reviews, by your company’s data manager, to determine data quality and track the progress. 

These suggestions can help you improve the quality of your data. Later on, you can start implementing more tools or automating some of those processes. It’s worth noting that different errors causing poor data quality require different approaches, as well as data quality standards and regulations in your organization should be evaluated on a regular basis.

Quality Management for Quality Outcomes 

As you can see, management of data quality is a mix of people, processes, and tools. All these aspects serve as a starting point for developing standards, metrics, and criteria that all workers must adhere to from the minute they insert a piece of data into a system or retrieve a dataset from a third-party source. 

Investing in data quality is now a cost-effective method for avoiding wrong choices and unpredictable expenditures. Apart from all mentioned above, it’s also important to define where poor quality data comes from. The most common sources are transition from outdated systems, user errors, or merging of several companies. 

If poor data quality is discovered in your organization, you do not have to discard it entirely. Insights from poor-quality data might also help you improve your operations in the future. An excellent technique here is to assess your present data, identifying and correcting the source of your quality issues. 

You can also take a look at those companies who provide data annotation services, as well as help with data quality control. It is challenging to establish a corporate culture in which everyone is able to take responsibility for data quality. However, prevention is always better than cure. 

Final Words

The importance of high data quality rises every day despite the type of company, given that all the crucial procedures and strategic decisions rely on data. Keep in mind that maintaining high-quality data isn’t a one-time move. It’s rather a never-ending process. The tips discussed in this article will help you avoid fatal mistakes in business and take the first steps in your data quality management journey.  

While maintaining good data quality may appear to be a significant headache at first sight, it will always pay off in the end. As a result, you will be able to maintain an adaptable and flexible workflow. Plus, as your practice improves, you will be able to build a more robust digital-oriented company that can thrive in a dynamic global economy.

Also Read: Performance Management in the Workplace