Governance
Bridging the Gap: Data Governance vs Analytics Governance Explained
Over the past few decades, organizations have been awash with data. In order to effectively manage and monitor large volumes of data, the Data Governance framework started gaining widespread adoption. The Data Governance framework has since been deemed to be a trusted and essential model that has been in use to transform the raw data, […]
Data Compliance vs Data Governance
How Are They Different, Or Are They The Same? Gartner predicts that 80% of data and analytics governance initiatives will fail by 2027 due to inadequate strategic focus, and 83% of organizations view compliance as a strategic priority. Meanwhile, Corlytics says, regulatory penalties worldwide reached an all-time high of $19.3 billion in 2024, understanding the […]
Governance Challenges in Modern Data Platforms
Modern enterprise business strategies have become increasingly data-driven. With evolving data needs, enterprises have moved on from traditional data architectures like data warehouses and disparate siloes to more unified platforms for data management, like third-generation data lakes and data lakehouses. However, with evolving architectures, enterprises also face challenges in effectively governing and managing their data […]
Federated Data Governance for the Enterprise
Today, enterprises adopt AI and machine learning to derive insights from their datasets, and it becomes increasingly critical to focus on effectively governing them. As data regulations around the globe impose heavy penalties on non-compliance, modern enterprises must have adequate governance capabilities to prevent exposure. Large corporations have diverse data needs; with multiple application owners […]
Is Data Governance Part of Data Management?
As organizations acknowledge the importance of effective data handling, understanding the relationship between data governance and management is essential for handling data effectively. Many professionals in the fields of information technology and data management often find themselves asking: Is data governance part of data management? This blog aims to clarify these concepts and explore how […]
Eliminating lawsuits, fraud, and failure: Embracing AI risk management
This is the time-tested axiom of risk management that holds true across business verticals, from insurance and banking to healthcare and manufacturing. If you can identify risk by predicting failure, you can, to a large extent, prevent undesirable outcomes such as litigation, fraud, and lost revenue. (more)