What is a Look in Looker?

A "Look" is one of the most fundamental concepts in Looker, but the term itself can be a bit confusing if you’re coming from other analytics tools. Simply put, a Look is a single, saved report or visualization. Think of it as answering one specific business question, like "How many new users signed up last month?" shown as a line chart, or "What are our top-selling products by revenue?" presented in a table.

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This article will break down exactly what a Look is, how it differs from a dashboard, and guide you step-by-step through creating your first one. We'll also cover a few practical ways you can use Looks to get quick answers and keep your team informed.

What is a Look in Looker, Really?

At its core, a Look is the saved result of a single query you’ve built in Looker's "Explore" environment. An Explore is Looker's interface for exploring your data - letting you mix and match different data points to find insights. When you arrange a query you like, choose a visualization, and hit "Save," you’ve created a Look.

Here are the key characteristics that define a Look:

• It's a Single Visualization: A Look is always one thing - one chart, one graph, one table, or one numerical value. It isn't a collection of different reports.
• It's Based on One Query: Every Look is powered by a single underlying query built from an Explore.
• It's Saved and Reusable: The main benefit is that you can save your query so you don't have to rebuild it from scratch every time. Anyone with the right permissions can access and run the Look to see the latest data.
• It's Shareable: Have a specific insight about campaign performance you want to share with a manager? You can send them a direct link to the Look.
• It's the Building Block for Dashboards: This is the most important concept. You build dashboards in Looker by arranging a collection of individual Looks onto a single page.

A helpful analogy is to think of a dashboard as a cookbook. The cookbook itself is the dashboard - a curated collection of related information. Each individual recipe card inside that cookbook is a Look - a standalone set of instructions and an outcome that is useful on its own, but even more powerful as part of the larger collection.

Looks vs. Dashboards: What’s the Difference?

This is a common point of confusion for new users. While Looks and dashboards are built from the same data, they serve very different purposes. Getting a handle on their relationship is essential to using Looker effectively.

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A Look Is a Specific Answer

A Look is designed to answer one specific question. It’s focused and self-contained. You would create a Look to find the answer to questions like:

• "What was our daily website traffic from organic search over the last 30 days?" (A line chart Look)
• "Which sales representatives closed the most deals this quarter?" (A bar chart Look)
• "Can I see a list of unpaid invoices older than 60 days?" (A table Look)

When you navigate to a Look, all you see is that single visualization and its data. It’s perfect for detailed analysis or sharing a precise data point with someone.

A Dashboard Is a High-Level Overview

A dashboard is a collection of visuals - often including multiple Looks - arranged on one screen. It’s designed to provide a comprehensive, at-a-glance view of a business area or process. A dashboard tells a broader story by combining answers to multiple different questions.

For example, a "Quarterly Sales Performance" dashboard might contain:

• A bar chart Look showing deals closed per sales rep.
• A line chart Look tracking revenue over the past 90 days.
• A table Look listing the top 10 largest customers by deal size.
• A single-value Look showing the total quarterly revenue number.

Each component provides a piece of the story, but together on one screen, they give a leader a complete picture of performance without needing to pull up four separate reports.

Here's a simple breakdown:

• Look: The single brick.
• Dashboard: The entire house built from many bricks.
• Look: Answers "What were ticket sales last Friday?".
• Dashboard: Answers "How are our overall event ticket sales trending?".

How to Create Your First Look: A Step-by-Step Guide

Now for the practical part. Creating a Look involves defining your question, building the query in an Explore, and then saving your work. Let’s walk through building a simple Look to track daily user signups.

Step 1: Start from an Explore

Everything in Looker starts in an Explore. This is your canvas for asking questions. Your Looker administrator will have set up different Explores based on your company's data sources (e.g., "Users," "Orders," "Website Traffic"). For this example, you'd navigate to the appropriate section and select an Explore like "Users."

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Step 2: Select Your Dimensions and Measures

In the left-hand panel of the Explore, you’ll see all the available fields you can use, organized into dimensions and measures.

• Dimensions: These are the attributes you use for grouping or filtering your data. They answer the "who, what, when, where." For our example, a key dimension would be "Signup Date" so we can group our users by the day they registered.
• Measures: These are the quantitative, numerical values you want to calculate. They are often aggregations like sums, counts, or averages. For our example, the measure would be "User Count."

To build your query, you simply click on the fields you need. We'll click on "Signup Date" from our list of Dimensions and "User Count" from our Measures.

Step 3: Filter Your Data (Optional but Recommended)

Your query will pull all signup data from all time, which is probably not what you want. Use the "Filters" section to narrow the focus. In this case, we'll want to add a filter to the "Signup Date" field to be "in the past 90 days." This makes the report more relevant and speeds up the query.

Step 4: Run the Query

Once you’ve selected your fields and set your filters, click the Run button in the top right. Looker will query your database and return the results as a raw data table below.

Step 5: Choose and Customize Your Visualization

A table of numbers is useful, but a chart is often better for spotting trends. In the "Visualization" tab, you can choose from different charts.

• For our example of "Daily User Signups," a line chart is the perfect choice to show the trend over time.
• Click on the line chart option. Looker will automatically render the chart based on your data.
• Use the settings gear icon to make simple tweaks. You can change colors, add labels to the X and Y axes (e.g., "Date" and "Number of Signups"), and give your chart a title.

Step 6: Save as a Look

Once your visualization looks right and accurately answers your question, it's time to save it.

1. Click the settings gear icon in the top right corner and select "Save as a Look."
2. A pop-up will appear prompting you to give it a name and an optional description. Be very specific with your titles. A name like "Daily User Signups - Last 90 Days" is far more useful than "User Report 1."
3. Save the Look in a relevant folder (either your personal folder or a shared team folder).

That's it! You've successfully created a reusable, shareable report. You can now access this Look anytime, add it to a dashboard, or schedule it to be emailed to stakeholders.

Practical Use Cases for Looks

So, when would you use a Look instead of just building a dashboard? Here are a few common scenarios.

1. Answering Quick, One-off Questions

Your boss messages you: "Hey, can you quickly pull the number of users from Canada who signed up in the last week?" You don’t need a full dashboard for that. You can jump into an Explore, filter by country and date, save it as a Look named "Canadian Signups Last 7 Days," and send them the link. This process takes minutes and provides a direct answer.

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2. Prototyping Dashboard Tiles

Before adding a new chart to a high-visibility executive dashboard, it’s smart to build and test it as a standalone Look first. This gives you a less-pressured environment to refine the query, test different visualization styles, and ensure the data presented is accurate. Once you're confident it's right, you can add that finished Look directly to the dashboard.

3. Scheduled Reporting and Alerts

Looks are excellent for automated reporting. You can schedule any Look to be delivered via email on a recurring basis. For example, you can create a Look showing "Daily Sales Totals" and schedule it to be sent to the sales team leadership every morning at 8 a.m. This keeps everyone informed without them needing to log into Looker.

Final Thoughts

Looks are the fundamental content unit in Looker. Understanding them as single, storable visualizations that answer specific questions is the first step toward mastering the platform. They are the essential building blocks you'll use for everything from quick ad-hoc analysis to creating comprehensive, high-level dashboards.

Learning the workflow of an analytics platform like Looker - navigating Explores, distinguishing dimensions from measures, and configuring charts manually - can be very time-consuming. We built Graphed because we believe getting insights shouldn't require such a steep learning curve. Instead of manually building reports piece by piece, you can connect your data sources like Google Analytics, Shopify, and Salesforce and simply ask for what you need in plain English - our AI data analyst will build the entire dashboard for you in seconds.