Data Mesh gets a lot of discussion. Some see it as revolutionary—the first new data architecture thinking in years. Others view it as a dangerous backward slide to the chaos of data silos. The reality lies somewhere between—a big shift in architecture thinking with some inherent risk. A few good architecture practices help to realize the benefits while managing the risks. Published at: https://www.eckerson.com/articles/a-thoughtful-approach-to-data-mesh

Many machine learning projects fail because data scientists don’t have the right data. Techniques such as synthetic data is a novel algorithmic approach to address algorithmic risks. Published at: https://www.eckerson.com/articles/synthetic-data-for-ai-definition-risks-and-strategies

Many machine learning projects fail because data scientists don’t have the right data. Techniques such as synthetic data is a novel algorithmic approach to address algorithmic risks. Published at: https://www.eckerson.com/articles/synthetic-data-for-ai-definition-risks-and-strategies

Data orchestration uses caching, APIs, and centralized metadata to help compute engines access data in hybrid or multi-cloud environments. Data platform engineers can use data orchestration to gain simple, flexible, and high-speed access to distributed data for modern analytics and AI projects. Published at: https://www.eckerson.com/articles/data-orchestration-simplifying-data-access-for-analytics

Data access management (DAM) is the process of defining and enforcing policies that control access to application data throughout the enterprise. New approaches to DAM provide greater access and better protection through centrally managed policies that are universally enforced. Published at: https://www.eckerson.com/articles/data-access-management-zero-sum-game-over

This article, the third in a series, dives into the technologies that underpin modern approaches to location intelligence. It explores databases for industrial-scale geospatial applications, advanced business intelligence (BI) tools for exploratory analysis, and simple use-case specific platforms. Published at: https://www.eckerson.com/articles/location-intelligence-part-iii-enabling-technologies

The data mesh makes business domain experts the owners of their data, which they deliver as a “data product” to analytics teams using a self-service data platform and a federated governance framework. Published at: https://www.eckerson.com/articles/why-enterprises-should-implement-the-data-mesh-with-dataops

An operating model for data & analytics is critical for aligning resources across the enterprise and balancing the needs for agility and governance. An effective operating model is critical to data & analytics success and its creation and upkeeping should be the primary focus of a chief data officer. Published at: https://www.eckerson.com/articles/an-operating-model-for-data-analytics

In this article, Lawson Abinati lays out core principles for market positioning that apply across all industries, as well as to Business Intelligence (BI) professionals. Although many business intelligence (BI) managers see themselves as technologists first, unless they understand the soft skills of sales, marketing, and communication, they won't succeed professionally or make good on their organization's investments in BI. Published at: https://www.eckerson.com/articles/what-is-positioning-and-why-is-it-important

This article summarizes the major characteristics of a modern data architecture and serves as a guide for organizations that are in the midst of developing a new data strategy for the modern age. Published at: https://www.eckerson.com/articles/ten-characteristics-of-a-modern-data-architecture