Looker

What differentiates Looker from other similar products?

Looker helps our product team to grasp drop-offs, user activity, and feature acceptance.

What is your favorite aspect of this product?

With only a few criteria, comparing consumption across versions, sectors, or nations is simple.

What do you dislike most about this product?

LookML needed some deep funnel logic represented specifically.

What recommendations would you give to someone considering this product?

Looker lets you probe farther into user behavior if product insights count.

What differentiates Looker from other similar products?

Looker differentiates itself with its modeling layer (LookML), which provides a centralized, reusable approach to defining business metrics and data logic

What is your favorite aspect of this product?

My favorite aspect of Looker is its LookML modeling layer, which allows for consistent, reusable definitions of metrics and dimensions across all reports, ensuring data accuracy and reducing redundant work for teams.

What do you dislike most about this product?

What I dislike most about looker is its complexity for new users.

What recommendations would you give to someone considering this product?

I recommend investing time in learning LookML early on to fully leverage Looker’s modeling capabilities.

What differentiates Looker from other similar products?

Looker connects directly to a company's data warehouse (e.g., BigQuery, Redshift, Snowflake) rather than storing data in its own platform. This approach ensures that businesses are always working with the most up-to-date data, eliminating the need for data replication. Looker promotes collaboration with features like comments on dashboards and reports, making it easier for teams to share insights and make data-driven decisions collectively. This sets it apart from many tools that are more siloed.

What is your favorite aspect of this product?

My favorite aspect of Looker is its LookML modeling layer. It allows teams to define data models centrally, ensuring consistency in metrics, calculations, and reporting across the entire organization. This not only reduces the risk of errors but also empowers teams to create reusable, scalable data structures that can be easily modified or expanded as business needs evolve.

What do you dislike most about this product?

One common critique of Looker is its steep learning curve, especially when it comes to LookML. For users who are not familiar with coding or data modeling, it can be challenging to set up and customize the data models. This often requires a solid understanding of SQL and LookML syntax, which can be a barrier for non-technical users or teams without a dedicated data engineering resource.

What recommendations would you give to someone considering this product?

Looker relies heavily on LookML, a modeling language that requires some technical knowledge, especially in SQL. Make sure you have or can hire a team member (or work with a consultant) who is comfortable with LookML and data modeling. This will be crucial for getting the most out of the platform. Begin with a pilot project or a small team to test out Looker’s capabilities. Start by connecting to one data source and building a few simple dashboards. As you get more comfortable, you can gradually scale up to more complex data integrations and reports.