An especially important aspect of a company's business function is the quality of data that they are utilizing in order to make major decisions. While there are many components that are needed in order to ensure the success of a company, high data quality ranks near the top in the list of priority.
What Is Data Quality?
In simple terms, the quality of data refers to the assessment of the data's readiness to achieve its goals within the context of the business it serves. There are a number of factors that influence how high or low the quality of the data being used. This can include reliability, relevance, completeness and accuracy among other components. As time has progressed, many corporations are emphasizing data quality management more because of its direct relationship to how it can affect the company's bottom line.
This aspect of a business is important because the quality of data is often portrayed to be the reason there are mistakes, untruthful reporting and poorly made strategies. In addition, there can be residual economic damage with low quality data. For example, this can come in the form of expenses needed to correct packages shipped to the wrong addresses or compliance fines from inaccurate financial reports.
Data Quality Management
Managing data quality is a multi-faceted process in order to ensure that the data is viable and reliable. The first step in management tends to be identifying the effect on the business and potential outcomes. This is where rules are put in place, targets in performance are set and enhancement initiatives are put in place. This will begin to set the standard for how the data will be utilized.
Then, the data is measured based on the results. To ensure that the data is consistent and continually improves after each use, this cycle continues after the initial efforts to maintain proper quality have been made.
Ways To Improve Data Management
The first step to managing data is to identify the problem data. This can be alleviated by utilizing specialized software to perform quality checks. These quality checks will be able to determine the impact of a data breach and verify the data's accuracy. At this point, a proper quality program can be implemented.
Being mindful of bringing in data from foreign sources is also extremely important. Current financial models of the business need to be studied, and if a new source of data is to be used, that logic has to be transferable to the new system. Making sure that code translations and location structures are in place are also just as important.
Consolidating systems is also a great way to managing the quality of data. Companies tend to make the big mistake of using more than one system to track data. Not only is implementing different systems to manage data more expensive, but it can cause problems in the workflow and reporting. Instead, consolidating data into one system will ease a lot of the burden that comes with the consistent flow of data coming in and out.
Running frequent reports is also an important checkpoint to pass in management. A regular set of reports to review data consistently is essential to ensure it is of the highest quality and accuracy possible. Identifying the unexpected with data is important to avoid critical errors. In addition, having frequent reports being made provides the company with the opportunity to rectify any mistakes at the source if they are found. If a mistake is to be made, it is always better to catch those errors early.