What is Looker?
Who uses Looker?
Why developers like Looker?
Here are some stack decisions, common use cases and reviews by companies and developers who chose Looker in their tech stack.
Looker , Stitch , Amazon Redshift , dbt
We recently moved our Data Analytics and Business Intelligence tooling to Looker . It's already helping us create a solid process for reusable SQL-based data modeling, with consistent definitions across the entire organizations. Looker allows us to collaboratively build these version-controlled models and push the limits of what we've traditionally been able to accomplish with analytics with a lean team.
For Data Engineering, we're in the process of moving from maintaining our own ETL pipelines on AWS to a managed ELT system on Stitch. We're also evaluating the command line tool, dbt to manage data transformations. Our hope is that Stitch + dbt will streamline the ELT bit, allowing us to focus our energies on analyzing data, rather than managing it.
BI front-end to a Google BigQuery warehouse. Data exploration, dashboards, audience segmentation, workflow integrations. Can define audiences and take action via Webhook and Segment API integrations. Looker
I use Looker to analyze sales, marketing, and business data. Also great for operational dashboards and data discovery. Looker
- Zero-lag access to data
- No limits
- Personalized setup and support
- No uploading, warehousing, or indexing
- Deploy anywhere
- Works in any browser, anywhere
- Personalized access points