A Look at Looker
Two BI acquisitions made big headlines this year: Salesforce acquired Tableau and Google acquired Looker. Tableau has been at the core of my work for awhile, but I hadn’t heard much about Looker prior to Google’s purchase. However, since the acquisition, I’ve had a lot of time to develop with Looker on my own time and eventually in my client work. In this post, I’ll walk you through the tool and give some of my conclusions on its high and low points.
For the sake of a reference point, I am analyzing Looker’s capabilities partially with reference to Tableau, because that is what most of our audience is familiar with. However, I want to be clear that these are very different product offerings with what I consider to be very different audiences and agendas.
Before we get started with our look at Looker, it’s worth mentioning Google also has its own visualization product: Google Data Studio. My Tessellation colleague John already took a look at GDS and its comparison with Tableau, which you can read here.
What is Looker?
Looker is a BI platform that is focused on enabling users to easily explore and analyze data and then share those insights with others. The platform’s interface is divided into a 3 main sections:
How does it work?
Now let’s walk through some of the main steps to build a dashboard in Looker.
Connecting to Data
First, let’s talk through getting to the data you need.
If your data does not already exist in an explore in Looker, this will be a bit of a process. I’ll give the sparknotes. After enabling development mode, you can import your data source to a new view, either from a table or by scratch. Importing from a table will prompt Looker to auto-import each field in LookML and make its best guesses at the fields. This is a good starting point for your view, but usually needs finessing for a user-friendly interface in the eventual explore.
Once the view is to your liking, create a new explore in the data model and push it to production or continue working with it in development mode.
If your data source is already in Looker, this is a lot easier. Simply navigate to the explore you want and boom – you’re in.
Building a Visualization
Now let’s build a viz. Looker builds visualizations out of dimensions and measures selected from an Explore. You also have the option to filter or pivot values in the query. A query is run with the selected fields, and the visualization is automatically built from there.
The visualization type can be changed on the top visualization bar and the settings toggle can be used to customize. The customization options vary pretty widely between chart types, but you almost always have options for labeling values, showing legends, and showing/hiding an axis.
Once the visualization is finished, it can be saved either as a Look or saved to a Dashboard. Looks are separately published objects, but can also be consumed by zero to many dashboards in the same folder. Below I am adding the visualization to a new dashboard. Because it is not saved as a Look, this visualization will only be consumed by this dashboard.
Table calculations are similar to Tableau’s calculated fields but require all fields used in the Table Calculation to be in the active query. Meaning, if I want to create an IF statement using an Event Date, Event Date must be selected in the active query. Event Date could then be hidden from the visualization if it is not relevant, but all returned query rows would still be “fanned out” by Event Date. You can probably start to see how this scenario might cause some issues.
Note: Custom Fields, which are a new beta field type, are a bit more flexible in that they do not require all fields to be in the active query. These utilize most of same built-in functions and require specific permissions to create.
One thing that I think Looker does particularly well with Table Calculations is comparisons to prior periods. Below, I am using the
offset() function in a Table Calculation (this function is not available in Custom Fields) to find the previous row’s total order count. In this case, the previous row indicates the prior month’s order count.
Using the Single Value visualization type and enabling the Comparison setting will allow for a simple way to show change and add context to KPIs. This is one visualization type that I think is significantly less technically complex to create in Looker than other BI tools.
Dashboard objects are called Tiles. These are semi-floating objects which can be easily moved around or changed in size. Tile types include visualizations, published Looks, text objects, and filters.
Customization on these tiles is, admittedly, fairly limited. You have some control over the size of tiles, whether their titles show, and you can add notes or annotations to further describe the tiles. You cannot change how the text looks (outside of a few options to bold or italicize in text tiles), add or change color to the tiles or dashboard background, or insert images or company logos.
So after using Looker for awhile now, what are my favorite parts?
Where am I looking for more?
What's the verdict?
If you’re looking for a highly secure tool for users to do ad hoc analysis on IT-curated data sources, Looker might be a fit for you. However, if you have a wide variety of complex blending requirements without a reporting database layer, need greater speed to insight on a wide variety of data sources, or highly value a custom visualization component, you might find that Looker will have a more difficult time checking all of the boxes.
I think of Self-Service BI tools and platforms on a spectrum, ranging from Highly Governed to Highly Self-Serve. I place Looker on the highly governed end, and Tableau more toward the opposite. This isn’t to say that you can’t have a governed Tableau environment or a “wild, wild west” self-service Looker instance- you can absolutely have either of those things. Looker’s current functionality just leans more toward the traditional IT focus, as a moderate level of SQL and LookML development is required to make a proper data source or a highly customized dashboard.
As shown by recent developments, such as enabling custom fields, the platform is making big improvements toward a more customized experience. Regardless of which tool is right for you and your organization, we should all keep our eyes on Looker and what fantastic things they’ll continue to do under the Google umbrella.