IBM Data Governance vs SAS Data Governance comparison

IBM Data Governance is a comprehensive solution designed to help organizations effectively manage and govern their data assets. Its primary use case is to establish and enforce data policies, standards, and rules across the enterprise.

The most valuable functionality of IBM Data Governance includes data classification, data lineage, and data quality management. Data classification enables organizations to categorize and label data based on sensitivity, ensuring compliance with regulations like GDPR. Data lineage provides a clear understanding of the origin and movement of data, facilitating data governance and decision-making. Data quality management ensures data accuracy, completeness, and consistency, enhancing overall data reliability.

IBM Data Governance helps organizations in several ways. Firstly, it improves data visibility and control, enabling organizations to understand their data landscape and make informed decisions. Secondly, it enhances data security and privacy by enforcing policies and standards, reducing the risk of data breaches. Thirdly, it promotes collaboration and accountability among data stakeholders, fostering a culture of data governance. Lastly, it enables organizations to optimize data usage and value, leading to improved operational efficiency and better business outcomes.

SAS Data Governance helps you maintain a consistent set of policies, processes and owners for your corporate information - including big data sets in Hadoop and Impala. You'll spend less time managing your data - and more time managing your business.