Introduction

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.