As a Project Manager at IPC Global, I’ve led several Qlik Cloud implementations in the past year. Moving to a SaaS analytics platform brings new opportunities and new challenges, especially around governance, adoption, and multi-tenant environments. This checklist distills the key lessons we’ve learned.
Phase 1: Pre-Project & Stakeholder Alignment
Defining success metrics for Qlik Cloud (usage, adoption rate, time-to-insight)
Aligning on licensing model (Analyzer, Professional, Capacity, etc.)
Identifying key stakeholders and creating a RACI matrix
Data residency and compliance requirements
Phase 2: Data Strategy & Governance
Choosing between Direct Query vs. Data Load
Setting up proper space architecture (Managed vs. Shared vs. Personal)
Implementing section access and row-level security in Qlik Cloud
Data cataloging and lineage best practices
Phase 3: Application Development & Best Practices
Recommended folder/structure standards in Qlik Cloud
Scripting & reload optimization for cloud
Using Qlik Cloud’s new features (AI-assisted insights, automations, storytelling)
Performance tuning tips specific to cloud
Phase 4: Change Management, Training & Adoption
Effective training approaches for business users
Communication plan and success stories
Managing user licenses and monitoring consumption
Phase 5: Go-Live, Hypercare & Optimization
Cutover checklist
Post-go-live support model
Monitoring usage with Qlik Cloud Monitoring apps
Continuous improvement loop
What would you add to this checklist? Have you faced any unique challenges with Qlik Cloud implementations? Feel free to share your experiences in the comments.
