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8 Reasons Why You Should Never Neglect Data Quality

While most people may not realize, data quality can vary based on the number of sources and the methods used to collect given data. Even so, ensuring data quality is important for different digital transformation projects. These can include predictive analytics, customer personalization, AI applications, and even machine learning.

This guide will help you better understand data quality and why it is vital for your business.

Lianna Arakelyan
Lianna Arakelyan
Content Writer
Published:
November 15, 2021

Data quality is one of the most important investments for any company today. While most people may not realize, data quality can vary based on the number of sources and the methods used to collect given data. These factors can make it increasingly challenging to ensure the quality of data. Even so, ensuring data quality is important for different digital transformation projects. These can include predictive analytics, customer personalization, AI applications, and even machine learning.

This guide will help you better understand data quality and why it is vital for your business.

What Is Data Quality, and Why Is it Important?

Data quality can be defined as the degree to which collected data meets accuracy, completeness, validity, and consistency expectations. By measuring the quality level of collected data, an organization is able to identify errors in the data that can be resolved for the data to fit the intended use.

Whenever data fails to meet the expectations, it causes a negative impact on the organization’s customer service, key strategies, and even employee productivity.

Having quality data is key when it comes to accurate decision-making in a company. Data accuracy is an integral part of data quality. Therefore, one inaccurate data point can cause havoc in the entire project.

Using poor quality data can be a source of inaccurate analytics, operational issues, improper business strategies, and even economic damages. Some of these damages can include meeting the extra expense incurred from shipping products to the wrong customer, lost sales opportunities from wrong customer data, and getting fined because of improper regulatory or financial compliance reporting.

Data Quality, Data Management, Data Governance - How Does it All Fit?

Data quality, management, and governance co-exist in a somewhat symbiotic relationship where each is important to the other. While data quality focuses on the actual data, the use and status, data governance and management focus on governing the data and the authorities that manage and maintain control.

For effective data management and governance to be achieved, one needs to be working with high-quality data. On the other hand, it is difficult to achieve a high level of data quality without the right data management and data governance policies in place.

For instance, imagine a project aiming to improve a company's domain quality. For this to be done effectively, data quality and data governance principles must be employed, especially when dealing with a high volume of data and different software systems.

8 Reasons Why You Should Never Neglect Data Quality

It Gives accurate and Timely Information to Manage Services and Accountability

According to statistics, at least 60% of company executives have little confidence in the data used in the company.

Data confidence is one of the most important aspects of gathering high-quality data. With good data, a company has access to accurate and timely data that can be used for effective management of services and accountability.

Good quality data is easier to trust and understand. By having a data quality infrastructure in place, an organization can improve confidence in the data, making it easier to trust the decision-making process using the given data.

Good Information to Manage Service Effectiveness

Using high-quality data makes effective service management easier. When you have reliable data, you can know what areas of your service delivery need improvement and thus focus your energies to improve these areas. When you improve your service delivery, you improve how your business relates with your customers, which is essential for the success of any business. You can use data to better understand your customers, which helps you tailor your service delivery to meet customer expectations, and improves negotiation. This is only possible when you have quality data.

To Prioritize and Ensure the Best Use of Resources

Having reliable quality data ensures accuracy within the organization. With this data, an organization can accurately distribute resources for different projects based on the project's needs. The more you understand your data, the easier it is to distribute resources for different needs. When resources are used effectively, it minimizes waste and improves profit margins. Data quality reduces the amount of time and resources used inefficiently.

Report to Auditors and Inspectors Who Will Make Judgements About Performance and Governance

Having accurate, high-quality data makes it easier for auditors and inspectors to judge the data's performance accurately. With high-quality data, it also becomes easier to govern the data. Good quality data makes it easier for the management to accurately judge how different areas of an organization are performing, making it easier to implement improvement changes.

You Enjoy Data Consistency

When you have a strong data quality infrastructure in place, it is easier for an organization to ensure data consistency. This ensures that everyone in the organization has access to the same figures and congruent reports. It also ensures that the data shared in the different branches is harmonious, impacting better decision-making and fostering better working relationships.

Good Quality Data Foster Readiness

When you have good quality data, your organization experiences increased readiness for when something goes wrong. You are able to identify when the quality of data goes down thanks to the data quality infrastructure in place. Having access to quality data makes it easier for you to detect inconsistencies and outliers in new data, which helps to minimize the cost of the errors long term.

Maintaining Brand Reputation

The data you use in your business has a direct impact on your brand reputation. Brands work hard to build their name as reliable information experts in their niche, which is achieved using good quality data. With good quality data, a brand is able to comply with the ever-increasing data regulations, making it easier to protect the reputation of the brand.

Good Quality Data Saves Time

When you focus on gathering good quality data, you avoid having to spend quality time backtracking to correct an error in the data and double checking your results to ensure accuracy. This leads to saving valuable time that can be spent improving other areas of the business.

Conclusion

Data quality plays a vital role when it comes to the performance of a business and customer service. To ensure informed decision making and distribution of resources, company data needs to be accurate. With the points highlighted above, taking data quality seriously is more critical today than ever for the success of any business.

Written by
Lianna Arakelyan
Content Writer

Lianna Arakelyan is a content writer and digital marketing expert at MuchNeeded, with a knack for social media marketing strategy and implementation. She is extreme in her work with a deep goal of always being updated on online and offline marketing, technology and science news around the world.

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