https://store-images.s-microsoft.com/image/apps.18744.fe7ebe0d-05d4-49a8-8cca-0cc95386b8a0.fee13701-02cf-4299-b5a2-e0aa46e19c19.df96fbb1-651d-4ef6-91ef-74c2c04f1a3a
Qlik to Power BI Migration
ZS Associates, Inc
Just a moment, logging you in...
ZS AI-Powered Qlik to Power BI Migration Accelerator
Overview
ZS’s AI-powered migration accelerator streamlines Qlik to Power BI migration. It automates QVF scanning, SQL generation, relationship modeling, and reconciliation testing, delivering up to 80% efficiency in development and QA workflows.
Key Capabilities
- QVF Scanning & Data Warehouse Automation: Scans QVF files, generates text summaries, converts to SQL, and builds data models with up to 80% backend efficiency.
- Qlik to Power BI Transformation: Converts QVF to PBIB files, automating relationship modeling and visualization setup with 50–80% front-end efficiency.
- Automated Reconciliation Testing: Compares legacy and new reports for consistency, achieving up to 50% QA efficiency.
- Report Rationalization Agent: Classifies reports using traffic light system:
- 🟢 Green: High usage, <40% overlap – migrate directly
- 🟠 Amber: Irregular usage, >40% overlap – manual review
- 🔴 Red: No recent usage, <40% overlap – decommission
Benefits
- Accelerated time to market
- Improved developer productivity
- Standardized output
- Future-ready architecture
- Reduced migration risk
Use Cases
- Qlik to Power BI migration
- BI modernization
- Automated QA
- Legacy report rationalization
- Reporting standardization
Target Audience
- BI Developers and Architects
- Data Engineers
- Technical Project Managers
- Enterprise IT teams
Technical Requirements
- Qlik QVF file access
- Power BI environment
- SQL-based data warehouse
Contact Information
Satish Jha
Associate Principal, Microsoft Center of Excellence
Email: Satish.jha@zs.com
Piyush Rai
Manager, Microsoft Center of Excellence
Email: Piyush.rai@zs.com
Kumar Rahul Dev
Manager, Microsoft Center of Excellence
Email: kumarrahul.dev@zs.com
Sekilas
https://store-images.s-microsoft.com/image/apps.59787.fe7ebe0d-05d4-49a8-8cca-0cc95386b8a0.fee13701-02cf-4299-b5a2-e0aa46e19c19.08a9bb06-c01e-4e81-a646-17d8836ba219