Welcome to December 2024’s “Book of the Month” column. This month, we’re featuring “AI Governance Comprehensive: Tools, Vendors, Controls, and Regulations” by Sunil Soares, available for free download on the YourDataConnect (YDC) website. This book offers readers a strong foundation in AI governance. While the emergence of generative AI (GenAI) has brought AI governance to […]
Technical and Strategic Best Practices for Building Robust Data Platforms
In the AI era, organizations are eager to harness innovation and create value through high-quality, relevant data. Gartner, however, projects that 80% of data governance initiatives will fail by 2027. This statistic underscores the urgent need for robust data platforms and governance frameworks. A successful data strategy outlines best practices and establishes a clear vision for data architecture, […]
Data Governance & Information Quality (DGIQ) 2025 West + Enterprise Data World (EDW)
+ DATE: May 5-9, 2025 LOCATION: The Westin Anaheim Resort | Anaheim, CA ABOUT THE EVENT: The Data Governance & Information Quality (DGIQ) Conference is the world’s most comprehensive event dedicated entirely to Data Governance and Information Quality, and Enterprise Data World (EDW) Conference, produced in cooperation with DAMA International, has long been recognized as the most comprehensive educational conference […]
The Impact of Advanced Data Lineage on Governance
In today’s data-driven business landscape, data quality – the availability of usable and business-ready information – remains a significant and worsening challenge for many organizations. To mitigate these effects, businesses need swift resolution of data issues with transparent and trustworthy information. However, in our fast-paced digital environment, complex data architectures with more system variables make it difficult to understand the problems. […]
AI Data Governance Spotlights Privacy and Quality
The emergence of artificial intelligence (AI) brings data governance into sharp focus because grounding large language models (LLMs) with secure, trusted data is the only way to ensure accurate responses. So, what exactly is AI data governance? Let’s define “AI data governance” as the process of managing the data product lifecycle within AI systems. To keep it […]
Innovating with Data Mesh and Data Governance
Large organizations want to create a flexible environment to innovate and respond quickly based on new data insights. But at the same time, these businesses want some structure for good Data Quality, data fit for consumption, simplifying and speeding up data access. Using a data mesh, which is a decentralized data architecture (collecting, integrating, and analyzing […]
From Chaos to Clarity: How Metadata Shapes the Future of Data Management
Just as the sun serves as the gravitational center, orchestrating the dance of planets in our cosmic neighborhood, data governance stands as the cornerstone in the vast realm of data management. Without a doubt, it’s the gravitational force that holds everything together. Let’s dive deeper into this analogy. Imagine for a moment that our solar […]
Understanding Data Governance Maturity: An In-Depth Exploration
In the rapidly evolving landscape of data management, the concept of data governance has gained prominence as organizations strive to manage, protect, and leverage their data effectively. While developing and implementing a data governance program, it is important to consider how to measure the organization’s current state of data management and develop a plan for […]
Women in Data: Meet Liz Henderson, the Data Queen
The latest installment in our Q&A series with women leaders in data features Liz Henderson, aka the Data Queen. (Read our previous Q&A here.) Liz Henderson, also known as the Data Queen, has held many roles over the past two decades: head of data management, data governance director, chief data and analytics officer, business mentor, board […]
Getting Started with Data Quality
Imagine burning three trillion U.S. dollars. Businesses do this virtually every year because of poor data quality (DQ). In a data-driven age, organizations cannot afford to waste this time and money. Instead, they need to focus on achieving good data quality through a comprehensive program dedicated to business needs. But how does a company implement an effective […]