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The Hype Around Semantic Layers: How Important Are Standards?

There are several reasons why the notion of semantic layers has reached the forefront of today’s data management conversations. The analyst community is championing the data fabric tenet. The data mesh and data lake house architectures are gaining traction. Data lakes are widely deployed. Even architectural-agnostic business intelligence tooling seeks to harmonize data across sources. Each […]

Scaling Data Access Governance

The rise of data lakes and adjacent patterns such as the data lakehouse has given data teams increased agility and the ability to leverage major amounts of data. However, this ability comes with potential consequences. Constantly evolving data privacy legislation and the impact of major cybersecurity breaches has led to the call for responsible data […]

Data Mesh or Data Mess?

The ways in which we store and manage data have grown exponentially over recent years – and continue to evolve into new paradigms. For much of IT history, though, enterprise data architecture has existed as monolithic, centralized “data lakes.” More recently, as the role of data evolves and changes, so too does where that data […]

Boost Business Value with a Well-Defined Enterprise Analytics Strategy

As digital technologies spread their roots in the business world, organizations have access to more data than ever. This data becomes an essential organizational asset when utilized for enriching business strategies. But the process of turning data into insights is as important as the data itself. Hence, more and more organizations across sectors are deploying advanced analytics to grow […]

Establishing Connections and Putting an End to Data Silos

The global pandemic and the move to remote and hybrid workplaces have highlighted the importance of connections in an increasingly disconnected world. While the traditional office setting has become dispersed, business leaders must still connect everyone and everything within their organization. They must connect not only systems, data, and applications to each other, but also to their […]

The Evolution of Data Virtualization: From Data Integration to Data Management

Data virtualization was first introduced two decades ago. Since then, the technology has evolved considerably, and the data virtualization of yesterday bears little resemblance to the data virtualization of today. This is due to several facts beginning with the limitations of legacy infrastructure, the massive amounts of structured and unstructured data that organizations were collecting, […]

Databases vs. Hadoop vs. Cloud Storage

How can an organization thrive in the 2020s, a changing and confusing time with significant Data Management demands and platform options such as data warehouses, Hadoop, and the cloud? Trying to save money by bandaging and using the same old Data Architecture ends up pushing data uphill, making it harder to use. Rethinking data usage, storage, and computation is […]