Looker Data Visualisation: A Complete Guide

To harness the power of data, it needs to be understandable. In our digitised world, data is the key to unlocking deeper levels of understanding about the factors that drive business success. But data can be complicated — especially for large organisations that collect a vast amount across multiple channels.

This is where business intelligence and visualisation tools come in. They allow businesses to turn complex data sets into clear visualisations, and then act on them. The result is smarter decision-making, more streamlined processes, and a competitive advantage over businesses that fail to capitalise on this opportunity.

In this article, we’ll take an in-depth look at one of the most popular data visualisation tools on the market: Looker.

Read on to learn about:?

• Looker’s data visualisation capabilities
• Its key features and how they are used
• The pros and cons of choosing Looker over one of its competitors
• How your business can get the most out of this powerful tool

What Is Looker??

Looker is a data analytics and visualisation tool. It enables businesses to analyse, and explore their data through unique visualisations, helping them to turn raw data into actionable insights that drive smarter business decisions. It does so through powerful features such as integrated insights and data-driven workflows.

Launched back in 2012, in 2019 Looker was acquired by Google for $2.6 billion and is now part of the Google Cloud Platform. It’s a browser-based solution, so there’s no need to worry about installation or maintenance.

While Looker is well-known in the data visualisation world, direct competitors including Microsoft Power BI, Tableau and QlikSense might be more familiar to businesses. Though Google’s acquisition of Looker in 2019 is aiming to change that.

As you’d expect, Looker shares some core features with other popular data visualisation and business intelligence tools, such as the ability to:?

• Build custom real-time dashboards
• Connect to any SQL database
• Create custom applications
• Leverage embedded analytics
• Access a range of customer support options?

What Modelling Language Does Looker Use?

One of Looker’s key differentiators is LookML, its native modelling language. LookML is an SQL-based language, but it aims to improve on SQL’s shortcomings to help users write simplified and streamlined SQL queries. LookML is a modular, reusable language. And collaboration tools such as version control means that Looker users don’t have to start a script from scratch or spend ages trying to find what changed and when.?

Looker Blocks — pre-built data models designed to fit common analytics patterns — also prevent users from having to start from square one each time they want to create a data model. Users can select pre-existing models and modify them to their needs. This includes:

• Analytics blocks
• Source blocks
• Data blocks
• Data tool blocks
• Embedded blocks
• Viz blocks

Looker’s Data Visualisation

As the name suggests, Looker is all about data visualisation. In this section, we’ll run through some of its core data visualisation capabilities — and how you can use them to drive business success.?

Looks And Dashboards

• Looks are visualisations created and saved by users. Looks are created in Looker’s Explore section, which can then be shared and used across multiple dashboards.
• Dashboards allow users to place and view multiple Looks, graphs or tables in a single place. This allows users to, for example, view a range of different but relevant KPIs in the same way in one place. Dashboards are interactive and customisable. For instance, you can put several Looks into one dashboard and add a filter, acting as a master control that affects each Look within that dashboard in the same way.

Both Looks and dashboards can be shared with anyone, helping everyone get on the same page and view and understand the data easily.

Filtering Looks And Dashboards

Both Dashboards and Looks have filter functionality. Toggling Looks and Dashboards filters can also provide users with greater flexibility and specificity based on the filters’ hierarchies. For example, by selecting a Dasboard filter for a particular year, that filter would apply to all the Looks in that dashboard by default.

However, you can also choose which Looks within a dashboard are affected by that filter. This enables users to set a dashboard filter for a particular year, and then apply a separate filter specific to certain Looks and disable the default dashboard filter for them. This lets you the ability to apply a filter to all your Looks in one dashboard, or apply different filters to Looks within an overall Dashboard filter.

Types Of Visualisations

Looker features a rich variety of visualisations that allow you to present, read, and understand data in different ways, including:?

• Cartesian charts, i.e. any chart plotted on x and y axes, including column, bar, line, and scatterplot charts?
• Pie and donut charts?
• Progression charts, including funnel charts and timelines?
• Text and tables, including single value charts, single record charts, and word clouds
• Maps, including Google Maps
• Custom visualisations

There are also 40 visualisations available via Looker Studio, previously known as Google Data Studio, as well as custom visualisations created by Looker’s partners. As mentioned above, Looker’s blocks — and Viz blocks in particular — can be used to quickly and easily create data visualisations.?

Hosted by Looker, you can add them to your Looker instance, allowing for seamless visualisations with powerful functionality, including the ability to drill down, download, embed, and schedule data.?

Suggested reading: For a broader look at how you can leverage your company’s data to drive business success, take a look at our guide: 9 Practical Steps to Building Your Data Strategy.

Pros And Cons Of Looker Visualisations

Now you have a solid understanding of what Looker is and how it works, but how do you know if it’s the right choice for your business? In this section, we’ll look at some of the pros and cons of Looker visualisations.?

Looker Pros:

#1 Cloud-Based + Browser-Based

Looker has all the advantages you’d expect from a cloud-based data analytics platform, including advanced security, high performance, and seamless accessibility. And because you access it directly through your browser, you don’t need to worry about software installation or manual updates and maintenance.

#2 Easy Git Integration

Looker allows users to integrate the popular version control system Git, enabling multiple people to work on visualisations simultaneously, record changes, and manage file versions. Looker users can see changes made to data-modelling layers, jump back to them at any time, and create different version strands in repositories that developers can then work on.

While not set up automatically, the integration can be easily set up and provides a benefit other data visualisation tools don’t.

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