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 […]
Advances in Data Lakehouses
Data lakehouses encompass the best of data lakes and data warehouses, making it possible to handle all types of data or analysis. Its architecture allows for versatile data storage solutions, supporting structured data like databases, unstructured data such as text and multimedia, and semi-structured formats like JSON. It incorporates real-time data processing, enabling on-the-fly analytics and insights. […]
The Convergence of the Data Mesh and Data Fabric: Data Architecture’s New Era
The most meaningful development in contemporary data architecture isn’t the growing interest in the concepts of the data mesh and the data fabric. Instead, it’s the potential for convergence of these two architectural approaches into a single architecture that supports both decentralization and centralization of integrated data, local data ownership, universal accessibility, and top-down and bottom-up implementation methods. […]
Data Management Trends in 2025: A Foundation for Efficiency
In 2025, organizations face a pivotal moment in data management evolution. While core principles endure, their implementation is undergoing a radical transformation. Data management – the comprehensive collection of practices governing data – must now balance unprecedented opportunity with mounting risk. The potential impact is massive. The data and analytics market could reach $17.7 trillion, with an additional $2.6 to […]
Data Architecture Trends in 2025
A modern data architecture is required to support the data-driven organization that every enterprise wants to be. Without a solid data architecture – composed of the models, policies, rules, and standards you set for how data is collected, stored, managed, and used – your ability to attain a holistic view of your business, make informed […]
Strategies for Managing Data Debt in Growing Organizations
As organizations scale, data debt can accumulate silently, affecting productivity, efficiency, and decision-making quality. Data debt refers to the accrued cost of shortcuts and inefficiencies in data management that may have once seemed expedient but ultimately hamper long-term growth. Over time, whether it’s due to process changes, platform switching or growth, organizations find themselves boggled down […]
2024 DATAVERSITY Top 20
As we approach the end of another year, we here at DATAVERSITY have been busy analyzing our data and answering the big questions: What was the most popular content on our website and training center over the past 12 months? Which data management topics did you – our readers and students – seek out again […]
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 Architecture Online – Free Conference
DATE: July 23, 2025 LOCATION: Online ABOUT THE EVENT: The annual Data Architecture Online (DAO) event will cover key strategies and technologies you need to know in order to build and manage a modern Data Architecture. Tap into the combined expertise of several industry-leading professionals and connect with hundreds of data peers during this day […]
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. […]