Explaining the Need for Data Quality for Executives and Management

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If as an IT expert you understand what data quality means, and why it’s essential, but the management of your organization is not aware or doesn’t have the understanding of the importance of data quality, it is high time they knew because businesses across the globe are now moving to the era of data-driven evolution. It is clear that for data quality to be maximized, it must follow precise, consistent management from the executives.

To a considerable degree, many IT teams encounter challenges when attempting to gain support from the management for resources and processes required to efficiently improve data quality. If the executives have an above-average degree of technical competence, the competence may or may not apply to the complexities of data quality.

That’s why it’s important to build a plan to demonstrate to your management the significance of data quality. The pointers below will help:

The Significance of Data Quality in Practical Terms

You might consider data quality challenges in terms of database index problems or messy disk segment tables. Unless your executives work with you in the IT field regularly, there is a probability they don’t understand these fundamental concepts.

That’s is the reason you should talk about the significance of data quality using practical examples that are easy for anyone without broad technical experience to comprehend. For example, you might state that a data quality problem arises when a database includes several entries for the same customer. That’s a fairly straightforward issue to understand.

Likewise, you could address the example of foreign or unique characters within terms that are wrongly formatted. Possibilities are that the company’s management has seen this issue in action, and can acknowledge why this problem might trigger issues with data management.

The Quality of Data Impacts Customers 

Executives might be compassionate when you explain to them how data quality problems make your work tougher. But they are unlikely to be compassionate if they think the problem ends there, so a tougher work for you does not inherently mean a problem for the business.

But when you clarify that problems of data quality can also influence customers such as contributing to missing information or making it challenging for sales personnel to reach customers, executives are more likely to understand the necessity of preserving data quality.

Data Quality Problems are Becoming Tougher

Ultimately, you want to assure that your executives understand that data quality issues are not entity that will leave on their own, or that you will only have to cope with them. Contrary, they seem to grow broader in scope, due to the ever-increasing of data generated by enterprises. The need to incorporate data through diverse IT services and infrastructure comprising of multiple forms of legacy and new technology is also important.

Data Accuracy is an Ongoing Process 

For related reasons, it is necessary to emphasize that ensuring data quality isn’t a one-and-one form of operation. You cannot literally set up a new device or system and examine your data quality issues permanently fixed. Rather, data quality requires continual commitment, and also constant analysis and optimization.

This means you will require your executives to be on the ground with data quality for the long draw. One way to help them value the continuous nature of data quality is to reanalyze the data quality discussion regularly and present data to demonstrate how data quality improves over time and can be further improved.


If you need help, iData is here! You can also check out the Getting Started with Data Quality and Advancing Your Career in Data courses from the iData Quality Academy.

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