Looker vs Sisense: A Comparison of Embedded Analytics Solutions

In today’s data-driven world, businesses that can harness the power of intelligent insights are poised to drive innovation and stay ahead of the competition. As digital leaders, we constantly seek solutions that can seamlessly integrate with our existing systems while delivering robust analytical capabilities. Two standout players in the arena of embedded analytics are Looker and Sisense. Below, we’ll dive deep into a comprehensive comparison of these two technologies to help you make an informed decision,

The Need for Embedded Analytics

Before diving into the specifics of Looker and Sisense, it’s vital to understand why embedded analytics is crucial for modern businesses. Embedded analytics allows organizations to integrate powerful data visualization and analytics directly into their applications, making insights more accessible without disrupting the user experience. This empowers users at all levels— from executive decision-makers to frontline employees—with the data they need to drive meaningful actions.

Looker: A Modern Data Platform

1. What is Looker?

Looker is a next-gen data platform that allows businesses to explore, analyze, and share real-time business analytics easily. Its cloud-native architecture ensures scalability, flexibility, and seamless integration with modern data warehouses.

2. Key Features

• Live Data Connections: Looker connects directly to databases or data warehouses, enabling real-time data insights without the need to extract data.
• LookML: Looker's proprietary modeling language, LookML, abstracts queries to provide consistency and reusable business logic.
• Embedded Analytics: Looker provides robust APIs and SDKs for embedding analytics into your applications, dashboards, and portals.
• Data Governance: Centralized control over data metrics and definitions ensures consistency and compliance across the organization.
• Customization and Extensibility: Custom visualizations, extensions, and integration capabilities allow for tailored analytic solutions.

3. Pros

• Ease of Use: Looker’s intuitive interface ensures quick onboarding and minimal learning curve for users.
• Flexibility: Supports a wide range of data sources and is highly scalable to accommodate growing data needs.
• Governance: Strong data governance and centralized modeling reduce discrepancies and ensure data consistency.
• Community and Support: Looker boasts a strong user community and extensive documentation.

4. Cons

• Cost: Premium pricing compared to some competitors.
• Requires Expertise: LookML learning curve can be steep for non-tech savvy users.

Sisense: Simplify Complex Data

1. What is Sisense?

Sisense is an analytics solution that simplifies complex data analysis, enabling organizations to unbox total insights by consolidating data from multiple sources. Its hallmark is its ability to handle large volumes of data with remarkable efficiency.

2. Key Features

• In-Chip Technology: Sisense’s architecture leverages in-chip technology to maximize CPU efficiency, speeding up query processing.
• Elastic Data Hub: Sisense Elasticube serves as its high-performance analytics engine, designed to handle massive datasets.
• Embedding and Customization: Offers extensive embed options with its JavaScript API and SDKs for tailor-made analytic experiences.
• Data Preparation Tools: Sisense provides robust tools for data cleansing and preparation, ensuring high-quality analytics.
• AI and Machine Learning Capabilities: Advanced ML integrations to enhance predictive and prescriptive analytics.

3. Pros

• Performance: Its in-chip technology offers unparalleled speed and efficiency when handling large data volumes.
• Comprehensive Tooling: Sisense includes extensive data preparation, ingestion, and visualization tools.
• Flexibility: Supports integration with a wide range of third-party tools and technologies.
• User-Friendly Embedded Analytics: Embedded analytics capabilities are robust and easy to implement with existing systems.

4. Cons

• Complexity: Setting up Sisense can be complex and may require significant expertise.
• Pricing: Similar to Looker, it’s on the higher end of the pricing spectrum.
• Customization: While powerful, the customization options can be overwhelming for new users.

Head-to-Head Comparison

1. Integration and Compatibility

• Looker: It excels in integrating with modern, cloud-based data warehouses and databases like Google BigQuery and Amazon Redshift. The live data connection is a significant plus for real-time analytics.

• Sisense: Shines with its wide third-party tool support, making it a versatile choice for businesses with existing, heterogeneous tech stacks. The Elastic Data Hub ensures that data from various sources are harmonized for analysis.

2. Performance and Scalability

• Looker: Provides real-time data insights by connecting directly to your data source. Scalability is inherent due to its cloud-native architecture.

• Sisense: Its unique in-chip technology provides outstanding performance, especially for extremely large datasets. Sisense is designed to scale both vertically and horizontally to meet growing data demands.

3. Data Modeling and Governance

• Looker: With LookML, users get a powerful modeling language that ensures consistency and scalability in data definitions across the business. Looker’s central data governance model is a favorite among enterprises needing strict compliance.

• Sisense: Offers robust data preparation and governance tools, though it may require more effort and expertise to achieve the same level of streamlined governance that Looker’s LookML provides automatically.

4. Usability and Customization

• Looker: Known for its ease of use, Looker offers a user-friendly interface that appeals to both technical and non-technical users. Customization, however, may require LookML expertise.

• Sisense: While powerful, new users might find Sisense’s extensive customization options overwhelming. However, for experienced users, it offers a more robust customization framework with its extensive APIs and SDKs.

5. Cost Efficiency

• Looker: Generally, it is positioned at the higher end of the pricing spectrum, which could be a consideration for smaller organizations or startups. However, its scalability and robust features often justify the investment for larger enterprises.

• Sisense: Similarly priced, Sisense offers a high ROI, especially for organizations dealing with large volumes of data and requiring heavy-duty analytics functionalities.

Conclusion

In the quest for the perfect embedded analytics solution, both Looker and Sisense offer impressive capabilities. The right choice depends largely on your specific business needs:

• Choose Looker if your business thrives on real-time data insights, cloud-native solutions, and a robust foundation in data governance. Its ease of use and strong community support are additional benefits.

• Choose Sisense if you deal with large datasets demanding high performance and require extensive customization capabilities. Its in-chip technology and versatile integration with third-party tools make it a powerful candidate.

At Deploi, we are committed to helping you navigate these decisions with clarity and confidence. Let’s transform your data into actionable insights with the right embedded analytics solution. Contact us to discuss how we can tailor these solutions to meet your digital roadmap and business ambitions.