Model Online / On-Site
Duration
Modules 4 modules

Course Objective

To enable organizations to adopt low-code and no-code platforms to overcome software delivery bottlenecks while preventing Shadow IT risks through sound enterprise architecture and workflow automation principles.

Participants master decision matrices for determining when to use no-code, low-code, or pro-code approaches and how to maintain a sustainable application lifecycle.

Target Audience and Prerequisites

  • Target Audience: Digital transformation leaders, business analysts, solution architects, IT managers, and process automation specialists.
  • Prerequisites: Basic understanding of business process modeling and general awareness of enterprise IT systems (ERP, CRM, and API concepts).

Key Takeaways and Focus Areas

  • Evaluating enterprise low-code / no-code platforms, architectural fit, and Total Cost of Ownership (TCO).
  • Structuring data models, user interfaces, business rule engines, and API integration layers for modularity and maintainability.
  • Governing Citizen Development operating models, Fusion Team collaboration, security guardrails, and AI-assisted workflow generation.

Curriculum

Low-Code / No-Code Ecosystem and Architectural Decision Matrix
  • Boundaries between no-code, low-code, and pro-code across app, process, integration, and data platforms
  • Use-case suitability scoring, vendor lock-in risk assessment, and licensing/TCO modeling
Application and Workflow Automation Design Principles
  • Decoupling data and presentation layers, state machines, and multi-stage approval workflows
  • REST/Webhook integrations, event-driven triggers, and exception/compensation handling patterns
Citizen Developer Operating Model, Fusion Teams, and Governance
  • Collaboration models uniting Citizen Developers with professional IT engineers (Fusion Teams)
  • Center of Excellence (CoE) structures, application criticality tiering, and data loss prevention guardrails
AI-Assisted Development and Application Lifecycle Management (ALM)
  • Leveraging generative AI assistants to scaffold apps, forms, and workflow automations from natural language
  • Dev-Test-Prod environment promotions, version control, technical debt mitigation, and app decommissioning

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