Qlik Sense vs Looker
Comprehensive side-by-side comparison of Qlik Sense vs Looker including features, integrations, customer segments, supported platforms, pros & cons, and company details. Find the best business intelligence software solution for your business needs.
Product Comparison
Qlik Sense
Data Analytics for Every Insight.
Looker
Data Insights, Simplified.
Description
Qlik Sense is a leading end-to-end data analytics platform designed to empower organizations of all sizes to make data-driven decisions. It provides a comprehensive suite of tools for data integration, preparation, visualization, and explorati...
Description
Looker, a Google Cloud product, is a modern business intelligence and data analytics platform designed to empower organizations to explore, analyze, and share data-driven insights. It utilizes a unique modeling language called LookML to create...
Videos (2)
Videos (1)
Use Cases
Use Cases
Made For
Made For
Key Features
- Reporting & Statistics
- Access Controls/Permissions
- Dashboard Creation
- Data Import/Export
- Data Visualization
- Reporting/Analytics
Key Features
- Multiple Data Sources
- Data Connectors
- Dashboard Creation
- Data Import/Export
- Data Visualization
- Reporting/Analytics
Industries
- Financial Services
- Healthcare
- Retail
- Manufacturing
- Telecommunications
Industries
- Retail
- Financial Services
- Healthcare
- Technology
- Manufacturing
Customer Segments
- Small Businesses
- Mid-size Businesses
- Large Enterprises
Customer Segments
- Small Businesses
- Mid-size Businesses
- Large Enterprises
Supported Platforms
- Web
- Mobile
Supported Platforms
- Web
- Mobile
Pros
- Associative Engine: Uncovers hidden insights by exploring all data relationships.
- Self-Service Analytics: Empowers users of all skill levels to create and share insights.
- Scalable Architecture: Supports growing data volumes and user bases with Kubernetes-based deployment.
Cons
- Complexity for Advanced Users: While user-friendly, advanced features may require specialized training.
- Potential Cost: Enterprise-level features and scalability can be expensive.
Pros
- Centralized Data Modeling with LookML: Ensures data consistency and a single source of truth.
- Powerful Data Exploration: Empowers business users to independently analyze data and discover insights.
- Scalability and Performance: Optimized for handling large datasets and complex queries.
- Strong Collaboration Features: Facilitates data sharing and teamwork across the organization.
Cons
- LookML Learning Curve: Requires specialized skills for data modeling and maintenance.
- Potential Cost: Can be expensive for smaller organizations or limited use cases.