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Data Product Success With Non-Invasive Data Governance

TDAN

The role of data products has become pivotal, driving organizations towards insightful decision-making and competitive advantage. However, ensuring the achievement of these data products demands the strategic integration of Non-Invasive Data Governance (NIDG).

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Data governance in the age of generative AI

AWS Big Data

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

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Product lifecycle management for data-driven organizations 

IBM Big Data Hub

In a world where every company is now a technology company, all enterprises must become well-versed in managing their digital products to remain competitive. In other words, they need a robust digital product lifecycle management (PLM) strategy. In addition, there is a downstream team that owns product transactional data.

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A Data Governance Ontology

TDAN

In the era where data powers digital transformation and informs the growing number of data products, it is critical that data practitioners have a common understanding of the things that make up a data governance program. The truth […]

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Why Modern Data Challenges Require a New Approach to Governance

A healthy data-driven culture minimizes knowledge debt while maximizing analytics productivity. Agile Data Governance is the process of creating and improving data assets by iteratively capturing knowledge as data producers and consumers work together so that everyone can benefit.

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Bringing an AI Product to Market

O'Reilly on Data

The Core Responsibilities of the AI Product Manager. Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. Product managers for AI must satisfy these same responsibilities, tuned for the AI lifecycle.

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Data Governance Maturity and Tracking Progress

erwin

Data governance is best defined as the strategic, ongoing and collaborative processes involved in managing data’s access, availability, usability, quality and security in line with established internal policies and relevant data regulations. Data Governance Is Business Transformation. Predictability.