

Sisense and Looker Studio are key players in the business intelligence tools category, each offering unique features. Sisense seems to have the upper hand in handling diverse data sources and providing robust analysis capabilities.
Features: Sisense is favored for powerful data integration, ease of use, and rapid deployment. It allows non-technical users to create custom analytics and provides a user-friendly setup. Looker Studio offers seamless Google services integration, ease of collaboration, and simplicity, ideal for teams utilizing Google's ecosystem.
Room for Improvement: Sisense could improve handling of large datasets and integration with tools like R. It lacks advanced settings for data manipulation. Looker Studio needs faster live data integration, a more sophisticated data modeling layer, and better scalability.
Ease of Deployment and Customer Service: Sisense provides flexibility with on-premises and cloud options and strong customer support, praised for its responsiveness. Looker Studio operates mainly in public and hybrid clouds. Its customer service is good but can improve in support communication.
Pricing and ROI: Sisense, perceived as expensive, offers a return on investment through reduced manual reporting and efficient business solutions. Looker Studio is mainly free, although additional integrations incur costs. Users appreciate its affordability but recognize the need for further expenses for complete data analysis.
| Product | Mindshare (%) |
|---|---|
| Sisense | 2.1% |
| Looker Studio | 2.5% |
| Other | 95.4% |


| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 3 |
| Large Enterprise | 6 |
| Company Size | Count |
|---|---|
| Small Business | 28 |
| Midsize Enterprise | 7 |
| Large Enterprise | 15 |
Looker Studio offers seamless integration with Google products, supporting business visualization and collaboration through efficient data management and analytics, catering to teams aiming for quick analytics solutions.
Looker Studio combines diverse data source integration including SQL and MongoDB with powerful visualization and custom filter creation. Users find its visuals clean and its platform user-friendly, enhanced by collaboration features and pricing. It aids decision-making and is popular for tracking metrics and analyzing sales funnels. Despite its strengths, users seek faster report loading, simpler data modeling, and better interface usability. Advertising system limitations, delayed data reflections, and integration challenges affect performance. Security and stability improvements alongside a richer data modeling layer are desirable, with pricing impacting large organizations.
What are the most important features of Looker Studio?Looker Studio supports business visualization for different industries, creating dashboards and reports for sales and marketing analysis. It's used to track metrics and sales funnels from sources like Google Sheets and BigQuery. Many companies integrate Looker Studio within web apps, providing data insights tailored to sectors such as e-commerce, finance, and more.
Sisense enables data visualization and analytics with ease of use and fast setup, effectively integrating different data sources for efficient decision-making.
Sisense provides an intuitive platform for companies to handle data visualization and advanced analytics without requiring extensive technical knowledge. Quick deployment, custom dashboard creation, and seamless embedding are supported by an API-first approach. It allows integration of data from multiple databases, enhancing speed through in-chip methodology and real-time updates. Users benefit from its ElastiCube Manager and reduced deployment time, contributing to data-driven decisions. Comprehensive documentation supports users in navigating potential challenges.
What are the key features of Sisense?Sisense is commonly used across industries such as product development, sales, and marketing to deliver tailored analytics and dashboards for diverse departmental needs. Organizations leverage Sisense's capabilities for embedding analytics, optimizing financial models, and improving sales strategies. Its intuitive interface allows non-technical teams to efficiently handle and derive insights from large datasets.
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