A Dynamic And Customisable BI Tool Perfect For Semantic Layers
March 20, 2024
A Dynamic And Customisable BI Tool Perfect For Semantic Layers
Score 8 out of 10
Vetted Review
Verified User
Overall Satisfaction with Looker
Some stakeholders use Looker to help visualise data that has been made available to them as part of our 'DaaP' programme (data as a product). The simple and intuitive nature allows simple connection to our data warehouse, native/cache'd querying, dynamic visuals, and an abstraction/semantic layer to sit between raw/modelled data and visulisation.
- Semantic layer
- Dynamic visualisations
- Intuitive design
- Can be slow at times
- Some features locked behind pricing tiers
- Semantic layer requires additional knowledge to use to full extent
- Allowing others to self-serve their own analytics and connect it to Looker simply and easily has helped unblock the central data team so they can instead focus on validated dashboards whilst stakeholders manage their day-to-day analysis themselves. Countless engineering hours have been freed up by not having to manage every user permission for each BI tool; we have a BYOBI approach; Bring Your Own BI
- Creation and management of a semantic layer (LookML =Looker Modeling Language ) allows peoples sandboxes and production databases to become clutter free. Minor adjustments, conditional fields, and even some modelling can all be done in LookML which doesn't need oversight or governance from the central data team.
- LookML, specifying drilldown fields and their sub-queries, as well as generally creating dynamic parameters with Liquid are all great features, but can have a steep learning curve. it may take some time to understand how to create this middle layer correctly, or even pose a risk of inheriting complex code from another source which can be unmaintainable if it becomes too big. Some level of governance is recommended if Looker is used by a large number of editors.
Looker is more mailable; it allows more dynamic visualisations, filters, drilldowns etc. It's sharing capabilities are also more streamlined than AWS Quicksight. However in contrast to this AWS Quicksight can leverage AWS IAM roles and policies which can be quite scalable. Looker permissions can be managed in the same way using their API, but requires that infrastructure to be maintained by an outside service (i.e. not native to Looker).
The number of visualisations in Looker are good in comparison, and the fact you can edit visualisations using LookML is great. In addition to this Looker can support Liquid, HTML, and some CSS - allowing lots of options for making clever, pretty dashboards.
The number of visualisations in Looker are good in comparison, and the fact you can edit visualisations using LookML is great. In addition to this Looker can support Liquid, HTML, and some CSS - allowing lots of options for making clever, pretty dashboards.
Do you think Looker delivers good value for the price?
Yes
Are you happy with Looker's feature set?
Yes
Did Looker live up to sales and marketing promises?
I wasn't involved with the selection/purchase process
Did implementation of Looker go as expected?
I wasn't involved with the implementation phase
Would you buy Looker again?
Yes