We use cookies to ensure that you have the best experience on our site.

What is Data cleansing?

Data cleansing, also known as data scrubbing, is the process of identifying and correcting errors, inconsistencies, and duplicate records within a dataset. It enhances data quality, improves accuracy in analytics, and ensures reliable outcomes in AI models and business intelligence systems.

Data protection officer
A data protection officer (DPO) is a professional responsible for ensuring an organization complies with data protection laws and privacy regulations. The DPO oversees security policies, conducts risk assessments, and serves as a liaison between businesses and regulatory authorities. Organizations handling large-scale personal data, especially under GDPR, are required to appoint a DPO to ensure compliance and safeguard user privacy.
Data verification
Data verification is the process of ensuring data accuracy, completeness, and consistency. It involves validating data against predefined standards, cross-checking sources, and detecting anomalies to maintain high-quality and reliable datasets for analytics and decision-making.
Raw data
Raw data refers to unprocessed information collected from various sources, such as sensors, databases, or surveys. It lacks structure and requires cleaning, transformation, and analysis before being used in decision-making, machine learning, or statistical modeling.