Elevate Data Quality


We live in a world where data is everywhere. Collecting and analyzing that data gives businesses a competitive edge in their respective industries. Organizations spend millions on improving their data quality by investing in novel tools and techniques, but they still suffer from severe data quality issues. The quality of data and information is fundamental to any company’s marketing and public relations department. Quality data helps support customer management, inform public policy, and increase public awareness about new products and services.

Here are ways your business can improve its data quality:ADP. Payroll – HR – Benefits

Using CRM

The business world has become highly competitive, with new brands entering now and then. The traditional methods of managing data will no longer be effective if you want to increase your market share. Using a well-designed, User-friendly CRM can help your business manage data effectively.

A CRM will allow you to maintain and manage your data without causing redundancies and inaccuracies. It can also help you visualize your company’s performance through charts and graphs. When your whole team has access to the CRM, they can keep one eye on how they perform and eventually fix it on their own. Using a CRM will also allow you to set metrics for judging employees’ performances, giving them a clear picture of what you expect.

Training and Reminding

Learning to enter data correctly is mandatory, whether for you or your employees. It would be best to make sure that your employees know how information needs to be entered, updated, and shared within the team. Building on our previous point, having a CRM will normalize how your company handles data. Your personnel will also appreciate the benefits of this training, as it will show how much you, as the manager, care about their learning.

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Data Quality Assessment

To improve data quality, you first need to measure it and identify what needs to be improved. The CIHI Data Quality Framework uses multiple data quality dimensions to query a particular data or holding aspect. The data quality dimensions are as follows:


Timeliness refers to how updated the information is at the time of release. Furthermore, it can be measured by measuring the gap between the end of the reference period (when you collected the data) and the date it becomes available to users. For example, timeliness is used when a data delivery from a source system conforms to a delivery schedule. Data in large delivery systems are available once processing is complete. However, if the processing is unsuccessful, it can delay data availability.


Numbers don’t lie. Relevant data can prove that the project you’re working on produces the best outcomes. It also supports your strategies for future improvements. In general, relevant data quantifies the purpose of your work. For example, you use big data in the medical industry to benefit medical agencies. It addresses issues such as forecasting epidemics and combating existing diseases more efficiently.

CorpNet. Start A New Business NowAccuracy

Lower levels of data accuracy at the start of any marketing campaign can lead to poor decision-making. Data can quickly become inaccurate, given the daily influx of people visiting online stores and e-commerce platforms. Identifying erroneous information is one of the most challenging data quality issues. For instance, a fair but inaccurate social security number can go easily unnoticed by a database.

However, this is why healthcare organizations should realize that quality is more important than quantity. Inaccurate information leads to poor service quality, which can cost businesses a significant amount of money.

Bottom Line

There is no getting away from the fact that data comes from everywhere nowadays. The list is endless, from mobile devices and social media to healthcare membership cards and market research. You must ensure that your organization’s data has integrity and is valuable enough to promote informed decision-making.

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