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What Is a Data Marketplace and Why Does It Matter?

The most successful organizations strive for excellence in their products, their processes, and especially in their workers. Excelling in a profession goes beyond simply meeting short-term and long-term goals to devising and applying creative, innovative solutions. To achieve this level of excellence, companies must provide their workers with the tools that let them convert their […]

Six Common Digital Transformation Challenges

During digital transformation, one of the most formidable challenges organizations face is resistance to change and the complexities of effective change management. Human nature often gravitates toward familiarity and routine, making any deviation a source of discomfort. This psychological inertia can stem from various factors including fear of job loss, perceived inadequacy in new skill […]

Foundations of Forensic Data Analysis

Forensic data analysis involves collecting, modeling, and transforming data to identify and highlight potential risk areas, detect non-standard or fraudulent activities that use data, and set up internal controls and processes to minimize a variety of risks. Data forensics can also be used in instances involving the tracking of phone calls, texts, or emails traveling […]

Combining Data Mesh and Data Fabric

Data silos represent a major business challenge, as noted by 60.9% of organizations in a recent Trends in Data Management survey. Without shared information, companies risk duplication, poor data quality, and missed opportunities for innovation. Consequently, many companies turn to modern and integrated data architectures. When doing so, organizations often consider two main approaches: data mesh and data fabric. Data […]

Implementing Data Fabric: 7 Key Steps

Understanding the importance of data integration is vital in the intricate process of implementing a data fabric. Data fabric architecture aims to create a unified and integrated environment for managing an organization’s data sprawl across various platforms and systems. Within this context, the data integration step ensures disparate data sources are seamlessly connected, enabling a fluid exchange […]