For years, organizations have invested heavily in dashboards, data warehouses, and centralized reporting platforms. Yet many still struggle to turn their growing volumes of data into real business results. The problem isn’t the data, it’s how we think about it. Business leaders must treat data not merely as an asset to be stored and queried, […]
Mind the Gap: Assessing Data Quality Readiness
This is the second in a two-part series exploring data quality and the ISO 25000 standard. OK. You’re with the program. You recognize that having quality data is important for accurate AI models. You would even concede that it’s important for other stuff too, but whatever, because AI is getting all the attention right now. […]
Best Practices for Automating Complex Unstructured Data Migration
In today’s data-driven business environment, enterprises are increasingly relying on sophisticated data migration strategies to manage and move vast amounts of information, particularly unstructured data. As enterprise IT infrastructure evolves, so too does the complexity of data migration. The scale, speed, and accuracy required to successfully migrate large datasets – often containing billions of files […]
Why One-Size-Fits-All Data Governance Doesn’t Work in the Age of AI
Data has evolved from a back-office function into a central driver of innovation, customer experience, and regulatory compliance. Yet, many organizations still apply a one-size-fits-all approach to data governance frameworks, using the same rules for every department, use case, and dataset. Here’s the issue: What works for managing a legacy HR system doesn’t work for […]
Dark Data: Surprising Places for Business Insights
A recent AI and Information Management report has shown that 64% of organizations manage at least 1 petabyte (PT) of data, and 41% manage at least 500 PTs. In itself, this is perfectly fine – data is the new oil, after all. The problem is, however, that anywhere between 40% and 90% of this data ocean remains dark, which […]
Change Data Capture and the Value of Real-Time Data Integration
Business insights are only as good as the accuracy of the data on which they are built. According to Gartner, data quality is important to organizations “in part because poor data quality costs organizations at least $12.9 million a year on average.” So, we believe that it stands to reason that providing access to the […]
From Parchment to Python: How Smart Data Evolved to What It Is Today
Data used to be a physical thing, stored on paper and in ledgers. Security was also a physical thing, with valuable data protected by actual locks and guards. Today, we navigate a landscape dominated by code, algorithms, and digital streams of data, a far cry from those early days. Yet, despite these transformative changes, the […]
The Rise of the AI Data Engineer
Although it’s a rewarding career, the job of chief data officer (CDO) comes with a long list of challenges, including massive data volumes and complexity, lack of high-quality data, privacy regulations, executive alignment, artificial intelligence (AI) and machine learning integration, and bridging the gap between technical data expertise and business objectives. What’s more, CDOs struggle […]
DGIQ + AIGov Conference: Takeaways and Cross-Cutting Topics
In this series of blog posts, I aim to share some key takeaways from the DGIQ + AIGov Conference 2024 held by DATAVERSITY. These takeaways include my overall professional impressions and a high-level review of the most prominent topics discussed in the conference’s core subject areas: data governance, data quality, and AI governance. In the first three […]
Data Fabresh: The Fusion Between Data Fabric and Data Mesh
In a world where data is the most valuable asset for decision-making, companies are looking for approaches that allow them to optimally manage, govern, and leverage information. Data “fabresh” has emerged as an innovative model that combines the best of data fabric and data mesh, fusing technological robustness with a decentralized organizational approach. What Is […]