Secrets of Data Analytics Leaders

Responsible AI ethical principles provide a clear, unifying purpose for the technological, business, and social goals of AI initiatives. Published at: https://www.eckerson.com/articles/the-opportunity-and-risk-of-generative-ai-part-iii-responsible-ai-ethics

This podcast explores the difference between data assets and data products, emphasizing the importance of properly labeling and categorizing different types of data assets. It discusses the role of internal data stores in creating and sharing data products, and the benefits they offer such as improved access to core data assets and streamlined processes. Additionally, it delves into the difference between data assets and data products, and how they serve a target audience with governance and testing.

Responsible AI can help data leaders comply with the fast-evolving regulatory environment of data and artificial intelligence. Published at: https://www.eckerson.com/articles/the-opportunity-and-risk-of-generative-ai-part-ii-how-responsible-ai-assists-compliance

US frontier history had races, risks, and rewards. Generative AI's future will follow a similar path. Published at: https://www.eckerson.com/articles/enterprise-data-and-the-taming-of-the-generative-ai-frontier

Dan and Jay discussed the concept of Data Fabric, an automated and AI-driven approach to managing modern data environments.

Simba Khadder and Kevin Petrie discuss strategies to overcome technical debt in implementation, the pivotal role of data in the success of ML projects, navigating regulatory compliance in machine learning, and the future of AI governance.

Learn how to attain an optimal return on investment (ROI) with MDM by choosing the appropriate architectural strategy and evaluating progress during the initial project implementation. Published at: https://www.eckerson.com/articles/driving-roi-with-master-data-management-part-ii-your-first-project

As organizations strive to meet the ever-growing demand for data, they are adopting data products to streamline delivery and ensure solutions provide value to business stakeholders. Learn about four traps that can disrupt data product development and how to avoid falling into them. Published at: https://www.eckerson.com/articles/four-traps-to-avoid-when-developing-data-products

Generative AI brings a promise to improve lives in a blistering innovation race, but also a threat to people, corporations, and even nations. Data analytics leaders must understand the risks of generative AI, both societal and business-related, to use it positively and avoid the destructive consequences seen with nuclear energy development. Published at: https://www.eckerson.com/articles/the-opportunity-and-risk-of-generative-ai-part-i-a-nuclear-explosion

The unbundling of the data ecosystem is causing organizations to “duct tape” products and frameworks together to build their solutions and data delivery processes. Organizations fail to build and deploy end-to-end, automated, repeatable data-driven systems, ignoring data engineering & dataops principles as well as best practices. Published at: https://www.eckerson.com/articles/dataops-in-data-engineering