Exploring data observability’s limits in data migration, integrity audits, and the need for specialized tools for reliability.

Published at:

https://www.eckerson.com/articles/the-shiny-allure-of-data-observability-its-limits-in-data-migration-integrity-audits-and-certification

A strategic approach to data monetization covering key processes, risks, and organizational shifts needed for success.

Published at: https://www.eckerson.com/articles/unlocking-data-monetization-success

A fresh perspective on data architecture, advocating for an 'anti-monolith' approach inspired by engineering best practices.

Published at: https://www.eckerson.com/articles/good-data-architecture-anti-monolith

Many practitioners view data mesh and data fabric as mutually exclusive approaches to data strategy. However, these paradigms complement each other. Data mesh focuses on decentralization and autonomy; Data fabric ensures centralized integration and governance. Let’s dive into how blending elements of both can offer flexibility and control to create the right fit for your organization’s data strategy.

Published at: https://www.eckerson.com/articles/blending-data-mesh-and-data-fabric-crafting-a-balanced-data-strategy-2118cd34-e463-4468-b150-bdaf9e1c541d

As organizations grapple with data spread across various storage locations, solutions like Coginiti Hybrid Query offer a much-needed alternative to fragmented tools.

Published at:

https://www.eckerson.com/articles/a-novel-approach-for-reducing-cloud-data-warehouse-expenses-from-coginiti

This blog post explores the evolving landscape of data catalogs, highlighting ten key market trends driving the adoption of next-generation solutions.

Published:

https://www.eckerson.com/articles/ten-key-market-trends-in-next-generation-data-catalogs

Data teams must filter, blend, and refine raw data inputs to create the high-octane fuel that drives innovation with artificial intelligence and machine learning (AI/ML).

Published at:

https://www.eckerson.com/articles/refining-the-right-fuel-how-data-integration-drives-the-ai-ml-model-lifecycle

With numerous data catalog options available, all claiming to be the best, how do you make an informed decision without exhaustive research?

Published at:

https://www.eckerson.com/articles/unveiling-the-future-of-data-catalogs

This blog describes the need for data teams to establish a flexible yet well-governed data architecture to support dynamic AI/ML projects.

Published at:

https://www.eckerson.com/articles/multi-style-data-integration-for-ai-ml-three-use-cases

Many data leaders want to implement self-service, but don’t realize that they first have to implement the right architecture, governance, operating model, project delivery approach, data, and change management plan.

Published at:

https://www.eckerson.com/articles/self-service-is-the-outcome-not-the-driver-of-a-data-driven-organization