In today’s rapidly evolving business landscape, enterprises rely on data as the driving force behind informed decision-making, innovation, and competitive advantage. However, many organizations are grappling with legacy data platforms that impede their ability to fully unlock the potential of their data assets. Traditional systems often fail to keep up with the demands of modern business operations. They are burdened by the inefficiencies of siloed data, inflexibility due to centralized control, and poor data quality leading to inaccurate business insights. To address these challenges, organizations are embracing modern data platforms that offer greater agility, scalability, and adaptability in data management.
In this report, we highlight three distinct data management approaches that are gaining prominence in the industry – data fabric, data mesh, and data vault. Each approach addresses specific challenges in modern data management, providing a comprehensive framework for optimizing data integration, organization, and utilization. Moreover, the report provides a comprehensive playbook of best practices for enterprises seeking to build and leverage a modern data platform.
Scope
All industries and geographies
Contents
In this report, we examine:
Key characteristics of modern data platforms
Challenges that data leaders face due to legacy data architecture
Key data management approaches – data fabric, data mesh, and data vault
Enterprise considerations to build robust modern data platforms
The rising adoption of AI and ML has transformed the way enterprises use data, elevating its importance to an unprecedented level. Today, enterprises integrate data into every aspect of their operations to facilitate decision-making and drive innovat…
