
Designing data governance that delivers value | McKinsey
Jun 26, 2020 · Follow these principles to shift from a data-governance model of loosely followed guidelines to one that makes the most of digital and analytics.
Getting the data architecture right in banking | McKinsey & Company
Feb 28, 2025 · Does the data architecture need to be capable of supporting comprehensive data governance controls—including data stewardship, policy enforcement, and audit trails—across …
Elevating master data management in an organization | McKinsey
May 15, 2024 · Data governance models for MDM should be designed with clear roles and responsibilities, be managed by a governance council with representatives from different business …
Revisiting data architecture for next-gen data products
Oct 3, 2024 · Reference architectures, data governance models, and thoughtful technology implementation provide a road map for forward-thinking CIOs to choose the most suitable archetype …
Data ecosystems made simple - McKinsey & Company
Mar 8, 2021 · The success of a data-ecosystem strategy depends on data availability and digitization, API readiness to enable integration, data privacy and compliance—for example, General Data …
ESG data governance: A growing imperative for banks
Feb 8, 2023 · Create a data model to capture ESG data at the certificate level, including integration with third-party data providers (via APIs) and compliance with ESG data policies.
Putting data ethics into practice - McKinsey & Company
Feb 17, 2023 · Leaders can start by developing a comprehensive data risk framework that defines the guiding principles, risk inventory, policies and standards, and controls that govern the ethical usage …
Reducing data costs without sacrificing growth | McKinsey
Jul 31, 2020 · The company launched an integrated technology-modernization program that includes a shift from on-premises to a foundational cloud-first approach and a data operating model that builds …
How to build a data architecture to drive innovation—today and …
Jun 3, 2020 · Predefined data models from software vendors and proprietary data models that serve specific business-intelligence needs are often built in highly normalized schemas with rigid database …
Strengthening the R&D operating model | McKinsey
Jan 9, 2025 · That is, they could seamlessly integrate data-driven and AI-based inputs by designing an operating model based on five key elements: understanding patients, identifying targets, discovering …