Architecture Path · Leading Change · Step 6

Data Modernization Leadership

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A boardroom-grade program that equips an accountable data leader to own and drive enterprise data modernization: build the strategy, win the mandate and budget, govern the migration, and turn a legacy estate into an AI-ready, regulator-defensible platform.

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8
Modules
40
Chapters
VP / Director
Level
Capstone
Board-ready roadmap
The journey

Eight modules, one arc

The eight modules build cumulatively toward a real capstone. Watch the work move, and the value compound, at every stage.

M01-02MandateCase & sponsorshipM03-04StrategyTarget-state & roadmapM05GovernanceRisk & BCBS 239M06-07MigrationDelivery & FinOpsM08AI-readyValue & the boardLegacy estateAI-ready platform

Each module builds the capability the next one depends on, ending in a portfolio-ready capstone.

Outcomes

What you'll be able to do

Own the mandate

Secure sponsorship, authority, and funding for enterprise data modernization.

Win the business case

Frame modernization in board language: cost, risk, AI readiness, and value.

Design the target state

Choose architecture, cloud, and operating model with confidence and neutrality.

Govern the journey

Run a regulator-defensible, FinOps-disciplined migration that lands safely.

Prove AI readiness

Turn the platform into an AI-ready foundation and evidence realized value.

Lead with credibility

Present and defend a modernization strategy to the board and regulators.

Curriculum

8 modules, 40 chapters, ending in a capstone

Eight modules of five chapters each, sequenced so the material builds cumulatively to a real, portfolio-ready capstone. Expand any module for its focus and lessons.

01 The Lead Data Owner's Mandate

What the role actually owns, and how to secure the authority to deliver it.

  1. The Lead Data Owner role: accountability, scope, and limits
  2. Mapping the data estate you are accountable for
  3. Where modernization stalls: organizational and political failure modes
  4. Securing executive sponsorship and a funded mandate
  5. Positioning modernization as a board priority, not an IT project
02 Building the Business Case

Turn modernization from a cost line into an investment the board approves.

  1. Framing outcomes: cost-to-serve, risk, AI readiness, revenue
  2. Total cost of ownership: legacy versus modern platforms
  3. Quantifying risk and regulatory exposure in financial terms
  4. Building the investment thesis and phased funding ask
  5. Answering CFO, CRO, and board objections
03 Target-State Data Strategy

Design the destination: a governed, cloud, AI-ready data platform.

  1. Reference architectures: lakehouse, mesh, and hybrid
  2. Cloud and platform strategy under sovereignty constraints
  3. Vendor neutrality: evaluating platforms without an agenda
  4. Defining data products and the operating model
  5. Aligning the target state to AI and analytics ambitions
04 The Modernization Roadmap

Sequence the journey so value arrives early and risk stays contained.

  1. Current-state assessment and baselining
  2. Slice-based sequencing: proving value before scaling
  3. Dependency mapping and the critical path
  4. The 90 / 180 / 365-day roadmap the board can track
  5. Milestones, gates, and progress metrics
05 Governance, Risk and Regulation

Make the platform defensible to regulators and internal audit.

  1. Governance-first modernization: ownership and decision rights
  2. BCBS 239 for risk-data aggregation and reporting
  3. Regulatory landscape: GDPR, CCPA, DPDP, and supervisors
  4. Lineage, quality, and controls that reconstruct reporting
  5. Managing model risk and concentration risk
06 Migration and Delivery Governance

Govern the migration so it lands without breaking operations.

  1. Migration patterns: re-platform, re-architect, retire
  2. Change-data-capture and reconciliation during cutover
  3. Delivery in slices validated against the baseline
  4. Managing vendors, integrators, and internal teams
  5. Rollback, contingency, and protecting production
07 FinOps and Cost Governance

Ensure the move to cloud improves economics rather than inflating them.

  1. FinOps: cost visibility, attribution, and accountability
  2. Avoiding the cloud cost blowout
  3. Chargeback and showback across data domains
  4. Forecasting and guardrails tied to business drivers
  5. Reporting cost and value to the board
08 Capstone: A Board-Ready Modernization StrategyCapstone

Convert the modern platform into compounding, evidenced business value.

  1. Build the AI-ready foundation: governed, high-quality data
  2. Enable analytics and AI teams without re-creating silos
  3. Measure and communicate realized value
  4. Sustain the operating model beyond the program
  5. Capstone: present a board-ready modernization strategy and roadmap
Who it's for

Built for VP / Director Lead Data Owners driving modernization

Lead Data Owners

VPs and Directors accountable for a data domain or the enterprise data estate.

Heads of Data and CDaO office

Leaders in the chief-data-and-analytics function shaping strategy and governance.

Data and platform leadership

Directors of data engineering, architecture, and platform who must land modernization.

Risk and regulatory leaders

Leaders in risk, compliance, and finance who own the regulatory case for change.

Program formats

How you learn

Self-paced

Work through it at your own pace, with lifetime access to every module and the capstone.

Mentor-led cohort

A guided cohort with live sessions, reviews, and a peer group working the same path.

Private corporate

A closed cohort for your team, tailored to your platforms, domains, and priorities.

Portfolio-building

Every module produces an artifact; the capstone assembles them into a portfolio deliverable.

For teams

Bring it to your team

Run Data Modernization Leadership as a private, closed cohort tailored to your platforms, domains, and priorities, as part of building the architecture capability your organization needs.

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FAQ

Data Modernization Leadership - answered

Who is this program for?

Lead Data Owners at VP or Director level in large banks and financial institutions, and the data, risk, and platform leaders around them, who are accountable for driving enterprise data modernization.

Is this training or consulting?

It is a training and leadership-development program. It builds the strategy, judgment, and playbooks a leader needs to drive modernization themselves. Advisory and private workshops are available separately.

Do I need a technical background?

No. It is written for accountable leaders and treats architecture at the level a VP or Director needs to decide and defend, not implement.

How is it specific to banks?

It is built around BCBS 239, supervisory expectations, model and concentration risk, data sovereignty, and the board and regulatory scrutiny bank data programs face.

What is the capstone?

A board-ready modernization strategy and roadmap you can take to your own board, assembled from the module deliverables.

Self-paced or cohort?

Both, plus private bank cohorts and board and executive workshops.

Take the next step on the path

Enrol, enquire, or explore the full IC-to-Head of Data Architecture path.

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