Data Director · Asset & Wealth Management
Data Training for Asset & Wealth Management Directors
You already know how to run a data function. What you need here is the sector layer: how asset managers, private banks and wealth platforms actually make money, who the players are, what MiFID II, PRIIPs or ESMA reporting mean for your data architecture, and which figures your board actually cares about. This page gives you that context alongside the core data curriculum, so you stop translating generic frameworks into your world and start applying them directly.
You get interactive tools to test scenarios specific to portfolio data and client reporting, a playbook built around real decisions you'll face this quarter, and an assessment that benchmarks your maturity against other data leaders in wealth and asset management. No filler, no theory disconnected from your P&L.
31 lessons · ~6 h · resumes where you left off
Your program
A focused program built on your vertical's content: the sector first, then your discipline applied to it.
The generalist Data track
The full craft of the discipline, beyond your sector.
More resources
Interactive tools
Frequently asked questions
Who is this data training for asset and wealth management built for?
It targets people who already run a data function (data directors, heads of data, CDOs) inside asset managers, private banks or wealth platforms. The core data curriculum assumes you know the discipline; what gets added is the sector layer — how these firms make money, who the players are, and how regulation shapes data architecture. If you're learning data fundamentals from scratch, the generic curriculum is the better starting point.
What's the difference between this page and the general data curriculum?
Same core data curriculum, plus a sector layer specific to asset and wealth management. That layer covers the economics of the industry, the main players, what MiFID II, PRIIPs and ESMA reporting imply for your data architecture, and the figures a board in this sector actually looks at. The point is to skip the step where you translate a generic framework into your own context.
Do I need a background in finance to follow it?
No. The sector fundamentals are covered from the ground up: revenue models of asset managers and private banks, the competitive landscape, and the regulatory constraints that land on data teams. A data director arriving from another industry gets the context; someone already in wealth management can move through that part faster and focus on the data architecture and reporting material.
Is there a certification or diploma at the end?
No. There is no diploma, no state-recognised certification and no affiliation with a school or university. Reading is free and open; creating an account only saves your progress. What you take away is the material itself and the maturity assessment result.
Is there a certification or diploma at the end?
No. There is no diploma, no state-recognised certification, and no affiliation with any school or university. Reading is free and open; an account only saves your progress. What you keep is the material and your assessment result.
What does the maturity assessment actually measure?
It benchmarks your data maturity against other data leaders in wealth and asset management, rather than against a cross-industry average. That makes the gaps readable: you see where you stand on the dimensions that matter in this sector, including client reporting and portfolio data. It's a diagnostic, not a graded exam.
How do the interactive tools and the playbook fit together?
The interactive tools let you test scenarios on portfolio data and client reporting with your own assumptions; the playbook turns that into a sequence of decisions you're likely to face this quarter. Use the tools to size the problem, then the playbook to decide what to do about it. Neither is theory disconnected from the P&L.
What does the regulatory part cover for a data architecture?
MiFID II, PRIIPs and ESMA reporting are treated from the data side: what they require you to capture, reconcile and produce, and how that constrains your architecture and pipelines. The angle is operational rather than legal — not a compliance course, but what a data director has to build to keep these obligations serviceable.