Data cleanliness or hygiene, involves ensuring all organizational data is accurate, complete, follows predefined rules or standards, maintains data uniformity and more. To achieve this, automated systems, that leverage data profiling and cleansing processes are used. It is essential to ensuring both operational efficiency and resiliency and security as well. Highly regulated industries are more inclined to investing in data security investments to assist with their compliance efforts. Without accurate and reliable compliance reporting data, businesses open themselves up to significant compliance violations and associated financial penalties.
The importance of data cleanliness goes beyond helping to support smoother business operations. It is a core element of ensuring a strong cybersecurity posture. Cybersecurity threats, compliance failures and confidentiality breaches, are a few of the security risks that can occur if good data hygiene is neglected over time. Data classifiers need to be aware of where sensitive data resides in order to prevent breaches and detect cyberattacks.
Data cleansing requires an ongoing commitment and the ability to integrate data quality practices into every stage of the data lifecycle. From initial data collection and entry to storage, processing and analysis, proactive data maintenance steps need to be followed in order to keep data healthy and make the most out of the asset.