When it comes to data quality projects, the question that often arises is, “When will we be finished?”

However, if we acknowledge the fact that data quality deteriorates over time, with some customer data measures suggesting a decline of up to 25% annually, the answer becomes clear: “Never!”

Embrace a culture of data excellence by implementing robust data quality assurance strategies tailored to your organization’s needs.

Data quality requires an ongoing commitment

Data quality is an ongoing journey that requires continuous attention and effort.

The simple reality is that as soon as we stop addressing data quality issues, the data begins to deteriorate due to various factors such as business process issues, data capture errors, or simply the passage of time. For instance, a client changes jobs, but we still have their old work number and email address on record.

A holistic approach to data quality

This highlights the need for a holistic approach to data quality assurance.

To establish a robust data quality framework, the following components should be considered:

1. Tactical data quality “projects” aimed at conducting root cause analysis, addressing the underlying sources of poor data, and scrubbing the existing data to resolve specific issues.
2. Automated application of business logic to ensure the maintenance of new data in the required state, minimizing the risk of data degradation.
3. Ongoing monitoring of data quality against agreed-upon metrics, allowing for proactive identification and remediation of any emerging issues.

It’s crucial to recognize that a sustainable data quality solution should become an integral part of the business-as-usual (BAU) process. Data quality cannot be achieved through a one-time project; it requires a consistent and repeatable approach that involves both business and IT stakeholders.

Get insights into building a robust data quality framework blueprint for sustainable data governance practices.

Now learn when is the best time to start a data quality program and set a roadmap for comprehensive data quality initiatives.