Looker vs. alternatives in 2024

18 September 2024 | 3 minutes of reading time

A few years ago, Looker emerged as a standout BI platform, back then known for its powerful semantic layer, integration with cloud data warehouses and great governance capabilities. However, the landscape has changed significantly, driven by tools, which handle data transformations directly in the data warehouse. This shift has led to a new, modern data architecture approach —one that emphasizes keeping the BI tool as “dumb” as possible by focusing on data visualization and serving, while offloading complexity and transformations to tools like dbt Cloud.

Why the “Dumb” BI tool approach works in 2024

The “dumb” BI tool approach focuses on using dbt (or another transformation solution) for all data modeling and transformation, with BI tools primarily used to visualize and serve the data. dbt centralizes transformations in the warehouse, making the data cleaner, more reliable, and easier to manage. This setup minimizes the need for complex semantic layers within the BI tool, reducing the risk of inconsistent or conflicting business logic between dashboards or between different tools consuming the data.

By offloading this work to dbt, the BI tool becomes a simpler, more focused component in the stack. This approach is a future-proof solution because:

  • It simplifies maintenance by reducing complexity and ensuring all transformation are centralized
  • It scales efficiently, as dbt can handle large transformations, while the BI tool serves pre-modeled data.
  • It future-proofs your stack by decoupling the transformation layer from the BI tool, making it easier to switch tools as needed.

This modern data architecture aligns with current trends and is likely to remain relevant as data stacks continue to evolve.

Alternatives to Looker: PowerMetrics, Power BI, and GoodData

For new projects, several alternatives to Looker fit well with the modern approach of using dbt for data transformations:

  • PowerMetrics: Designed for real-time metrics and ease of use, making it an excellent option for teams seeking fast deployment and self-service reporting.
  • Power BI: Known for its affordability and seamless integration with Microsoft products, it offers robust analytics with a highly intuitive interface.
  • GoodData: A strong option for embedded analytics and governance, integrating smoothly with dbt to handle data modeling and business logic on top of transformed data.

These tools work effectively within a dbt-driven workflow, aligning well with the strategy of centralizing transformations in dbt, while still providing flexible and powerful options for delivering insights and business analytics.

Looker vs. Looker Studio

When discussing Looker, it’s important to distinguish between Looker and Looker Studio (formerly Google Data Studio). Looker is a full-featured BI tool designed for complex data needs, while Looker Studio is a more lightweight, free tool for simpler dashboards. For more details, refer to our in-depth article comparing these versions.

Why should I stick with Looker?

While Looker is no longer the automatic first choice, it still offers significant value for organizations that have invested in it. Here’s where Looker excels:

  1. Self-Service Exploration: Looker allows business users to explore data in an ad-hoc manner without technical skills, offering more flexibility than many simpler BI tools.
  2. Customization and Advanced Visualizations: Looker provides deep customization options, allowing teams to build tailored dashboards and reports for specific use cases.
  3. API and Data Applications: Looker’s API allows teams to build custom data applications, making it more flexible than many alternatives.
  4. Google Cloud Integration: For organizations using Google Cloud services, Looker’s seamless integration with BigQuery and other tools reduces friction in data operations.
  5. Enterprise Governance and Security: Looker’s governance and security features are robust, making it an ideal choice for regulated industries that require fine-grained control over data access. It also provides native Git version control.

Conclusion: choosing the right BI tool in 2024

The business intelligence landscape has shifted, and Looker is no longer the clear frontrunner. Alternatives like PowerMetrics, Power BI, and GoodData offer strong solutions that align with the modern trend of moving complex data transformations upstream to tools like dbt. This approach leaves the BI tool to focus on serving clean, transformed data.

However, for those already using Looker, it remains a valuable tool, particularly with its strengths in self-service exploration, customization, API integration, and enterprise governance. These features still make Looker a compelling choice for organizations that need more advanced control and flexibility.

The key takeaway is that heavy data transformations should be handled outside the BI tool, upstream in the data pipeline. This strategy allows the BI tool to focus on visualization and serving insights, ensuring a more flexible, scalable, and future-proof data stack as your organization’s needs evolve.