This next manifestation of centralized data strategy emanates from past experiences with trying to coalesce the enterprise around a large-scale monolithic data lake. In many cases, this created a ...

Data-driven abilities are at the core of an organization’s digital transformation and AI journey. However, according to research, only 30% of companies have a well-articulated data strategy, and ...

For decades organizations chased the Holy Grail of a centralized data warehouse/lake strategy to support business intelligence and advanced analytics. Now, with processing power built out at the ...

For years, cloud computing was synonymous with centralization. That era is over. Enter: the distributed cloud.

This article explores why centralized data warehousing remains the better choice for long-term data strategy and why data mesh may not live up to its promises. Why This Discussion Matters. As data ...

• Centralized data is easier on marketing budgets. When a business runs on a data-centric model, it’s easier and quicker to pinpoint initiatives that aren’t producing results.

When data is fully centralized and managed by a core data team, compliance and security are managed in tandem with secure integrations, user control and detailed logging. Real-world application : For ...

Data architecture, engineering and management have historically concentrated on bespoke centralized systems. Enterprise data teams concerned themselves with data warehousing and application databases.