Data Digest

Filter by

search
abstract image for AI agent governance

Blog

Data Governance for AI Agents: What You Need to Know

Artificial Intelligence (AI) agents are rapidly transforming industries, offering unprecedented capabilities to automate tasks, analyze data, and drive decision-making processes. These intelligent systems leverage machine learning algorithms and vast amounts of data to perform complex operations, often surpassing human capabilities. However, as AI agents become more sophisticated and ubiquitous, the need for robust data governance frameworks has emerged as a critical concern.

finance district, city view

Blog

Mastering Critical Data Elements (CDEs) for Financial Services: A Strategic Imperative

In today’s data-driven economy, financial institutions must effectively manage their most valuable data assets to ensure regulatory compliance, maintain operational efficiency, and drive business success. One of the most critical aspects of data management in the financial sector is the identification and governance of Critical Data Elements (CDEs). These are the specific data points essential to business operations, financial reporting, regulatory adherence, and risk management.

abstract data image

Blog

How AI Agents Are Revolutionizing Data Catalogs and Governance

Enterprises are navigating a profound data management crisis. Forrester Research found that "less than 0.5% of all data is ever analyzed and used" and projected that if the average enterprise could boost data accessibility by just 10%, it would generate more than $65 million in additional net income. 

basketball court

Blog

How the NBA Built a Data Product Operating Model to Drive Self-Service Analytics

In professional sports, data is a game-changer—and nowhere is that more evident than at the NBA. The league’s data strategy team has embraced a modern approach to data management, transforming raw data into a valuable asset for internal teams, from marketing to finance to product development. At the heart of this transformation is a shift to treating data as a product, paired with technology and governance processes that enable discovery, collaboration, and trust.

sports field

Blog

Data Governance by Design: Lessons from Fanatics Betting & Gaming

What does it take to build a high-performing, compliant, and scalable data organization—especially in a highly regulated industry like sports betting?

data leadership

Blog

The Future of Data Leadership: Why CDOs Must Evolve

For over a decade, data leaders have promised transformation: better decisions, stronger performance, and competitive advantage through data. But in today’s climate of tighter budgets and AI-driven urgency, data leaders are confronting a new reality: the need to deliver business outcomes – and fast.

data framework

Blog

Why AI Can’t Thrive Without Governance: A Strategic 4-Step Framework

The rapid rise of AI in the workplace is undeniable. In a recent McKinsey survey, 78% of respondents say their organizations are regularly using generative AI in at least one business function, up from 72% last year. AI offers immense value across a wide range of use cases, from automating repetitive tasks to generating creative content and powering data-driven decision-making.

words or LLMs

Blog

6 Key Steps to Using Large Language Models with Your Internal Data

The rapid evolution of artificial intelligence — and particularly large language models (LLMs) — has unlocked unprecedented opportunities for businesses to leverage their internal data in new ways. 

clouds

Blog

The Future of Cloud Optimization: Insights from Sync Computing’s CEO, Jeff Chou

As AI adoption accelerates, so do the challenges of managing the vast computational resources needed to power it. Cloud inefficiencies, soaring compute costs, and a growing reliance on GPUs make optimization a critical need for enterprises. 

1 of 64