A rising number of financial services firms are adopting the discipline of governed data integration to build 360-degree customer views. Published at: https://www.eckerson.com/articles/governed-data-integration-for-financial-services

Synthetic data and artificial intelligence (AI) complement each other but are both subject to the risk of AI bias. Consequently, companies need to implement architectural and governance controls to reduce the bias that synthetic data can inject into AI models. Published at: https://www.eckerson.com/articles/mitigating-the-risk-of-bias-in-synthetic-data-for-ai

As enterprises grow more dependent on the cloud and as the economy convulses, FinOps will soon become mandatory. Published at: https://www.eckerson.com/articles/the-rise-of-finops-cost-governance-for-cloud-based-analytics

Business domains have a range of data & analytics capabilities that enterprise data teams must support. The key is to ensure domain activity aligns with enterprise standards and best practices to ensure data consistency and avoid silos. Published at: https://www.eckerson.com/articles/an-operating-model-for-data-analytics-part-iv-red-team-composition

Active metadata is not a type of metadata, it’s a way of using metadata to power systems. Active metadata is a critical feature of modern data architectures such as data fabric and data mesh. It makes things work such as data access management, data classification, and data quality management. Published at: https://www.eckerson.com/articles/active-metadata-the-critical-factor-for-mastering-modern-data-management

This blog explores four use cases for data orchestration and examples of the supporting architectural elements. Published at: https://www.eckerson.com/articles/architecting-data-orchestration-four-use-cases

Exploring the roles and functions of blue and purple teams in enterprise data and analytics. Optimal team composition and dynamics for data analytics, centralized vs. decentralized models. Creating effective federated operating model without a Program Services department. Diverse team structures in data and analytics leadership for optimizing success. The crucial role of Spanners in building efficient data solutions.

Data observability provides intelligence about data quality and data pipeline performance, contributing to the disciplines of DataOps and FinOps. Vendors such as DataKitchen, DataOps.live, Informatica, and Unravel offer solutions to help enterprises address these overlapping disciplines. Published at: https://www.eckerson.com/articles/the-blending-disciplines-of-data-observability-dataops-and-finops

Hybrid development teams are critical to the success of a data & analytics program. Data leaders must invest time, energy, and thought to the creation of these teams and how best to support them. It’s critical that they allocate staff time to nurture knowledge flows between component groups. Published at: https://www.eckerson.com/articles/an-operating-model-for-data-analytics-part-ii-knowledge-flows

“Metadata is data about data” is a bad definition. It’s vague and recursive. It’s like saying climate is the weather of weather. But if metadata is not data about data, then what is it? Follow my thought process working toward a better understanding of metadata and its role in today’s data landscape. Published at: https://www.eckerson.com/articles/fixing-metadata-s-bad-definition