DCAM® v3 Pocket Guide
Learn what DCAM is, why it matters, and how to improve your organisation’s data management capability. Download Ortecha’s practical DCAM Pocket Guide for implementation tips, maturity insights and real-world advice.
Untangle Market Data: What the First 30 Days Should Actually Look Like
Infographic | This 30 day action plan shows how to baseline spend, surface duplication and give leadership a defensible position to untangle market data.
The Market Data Blind Spot Costing Organisations Millions
Market data costs can run into the millions, yet few organisations can see the full picture. This article explores why spend, entitlements and risk stay hidden and how leaders regain control.
Automated Data Management: What Every CXO Needs to Know
On-Demand Webinar | This webinar cuts through the AI hype to show how leading enterprises are automating data management at scale — safely, pragmatically, and with real ROI.
Data Management That Thinks
Whitepaper | Why traditional data management and governance can’t scale. What replaces it? Automated Data Management.
DCAM® v3: Your Path to Data Excellence
Guide | We outline why the DCAM® v3 framework is the way forward to solving data headaches holding your business back.
DCAM® v3: The New Gold Standard for Data Management – Why It Matters Now
The EDM Association recently released their DCAM v3 framework. This blog outlines why it should be on the radar of every data leader today.
Strengthening Data Culture Across a Major U.S. Bank with DCAM
Client Story | A three-year DCAM journey that helped a major U.S. bank cut confusion, build clarity and set a stronger foundation for its data strategy.
How to define critical data
Whitepaper | The concept of a Critical Data Element (CDE) originated when BCBS 239 regulations were brought in to the Financial Service Industry. But there’s still uncertainty about how they should be designated and used. This paper takes you through best practice in this area.
Anatomy of a Data Management Operating Model
Guide | The 8 essential elements of a data management operating model, including clear capabilities and roles, supported by shared language and a strong data culture.
